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<div class="title">tensorNet.h</div>  </div>
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<a href="tensorNet_8h.html">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno">    1</span>&#160;<span class="comment">/*</span></div>
<div class="line"><a name="l00002"></a><span class="lineno">    2</span>&#160;<span class="comment"> * Copyright (c) 2017, NVIDIA CORPORATION. All rights reserved.</span></div>
<div class="line"><a name="l00003"></a><span class="lineno">    3</span>&#160;<span class="comment"> *</span></div>
<div class="line"><a name="l00004"></a><span class="lineno">    4</span>&#160;<span class="comment"> * Permission is hereby granted, free of charge, to any person obtaining a</span></div>
<div class="line"><a name="l00005"></a><span class="lineno">    5</span>&#160;<span class="comment"> * copy of this software and associated documentation files (the &quot;Software&quot;),</span></div>
<div class="line"><a name="l00006"></a><span class="lineno">    6</span>&#160;<span class="comment"> * to deal in the Software without restriction, including without limitation</span></div>
<div class="line"><a name="l00007"></a><span class="lineno">    7</span>&#160;<span class="comment"> * the rights to use, copy, modify, merge, publish, distribute, sublicense,</span></div>
<div class="line"><a name="l00008"></a><span class="lineno">    8</span>&#160;<span class="comment"> * and/or sell copies of the Software, and to permit persons to whom the</span></div>
<div class="line"><a name="l00009"></a><span class="lineno">    9</span>&#160;<span class="comment"> * Software is furnished to do so, subject to the following conditions:</span></div>
<div class="line"><a name="l00010"></a><span class="lineno">   10</span>&#160;<span class="comment"> *</span></div>
<div class="line"><a name="l00011"></a><span class="lineno">   11</span>&#160;<span class="comment"> * The above copyright notice and this permission notice shall be included in</span></div>
<div class="line"><a name="l00012"></a><span class="lineno">   12</span>&#160;<span class="comment"> * all copies or substantial portions of the Software.</span></div>
<div class="line"><a name="l00013"></a><span class="lineno">   13</span>&#160;<span class="comment"> *</span></div>
<div class="line"><a name="l00014"></a><span class="lineno">   14</span>&#160;<span class="comment"> * THE SOFTWARE IS PROVIDED &quot;AS IS&quot;, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR</span></div>
<div class="line"><a name="l00015"></a><span class="lineno">   15</span>&#160;<span class="comment"> * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,</span></div>
<div class="line"><a name="l00016"></a><span class="lineno">   16</span>&#160;<span class="comment"> * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.  IN NO EVENT SHALL</span></div>
<div class="line"><a name="l00017"></a><span class="lineno">   17</span>&#160;<span class="comment"> * THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER</span></div>
<div class="line"><a name="l00018"></a><span class="lineno">   18</span>&#160;<span class="comment"> * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING</span></div>
<div class="line"><a name="l00019"></a><span class="lineno">   19</span>&#160;<span class="comment"> * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER</span></div>
<div class="line"><a name="l00020"></a><span class="lineno">   20</span>&#160;<span class="comment"> * DEALINGS IN THE SOFTWARE.</span></div>
<div class="line"><a name="l00021"></a><span class="lineno">   21</span>&#160;<span class="comment"> */</span></div>
<div class="line"><a name="l00022"></a><span class="lineno">   22</span>&#160; </div>
<div class="line"><a name="l00023"></a><span class="lineno">   23</span>&#160;<span class="preprocessor">#ifndef __TENSOR_NET_H__</span></div>
<div class="line"><a name="l00024"></a><span class="lineno">   24</span>&#160;<span class="preprocessor">#define __TENSOR_NET_H__</span></div>
<div class="line"><a name="l00025"></a><span class="lineno">   25</span>&#160; </div>
<div class="line"><a name="l00026"></a><span class="lineno">   26</span>&#160;<span class="comment">// forward declaration of IInt8Calibrator</span></div>
<div class="line"><a name="l00027"></a><span class="lineno"><a class="line" href="namespacenvinfer1.html">   27</a></span>&#160;<span class="keyword">namespace </span><a class="code" href="namespacenvinfer1.html">nvinfer1</a> { <span class="keyword">class </span>IInt8Calibrator; }</div>
<div class="line"><a name="l00028"></a><span class="lineno">   28</span>&#160; </div>
<div class="line"><a name="l00029"></a><span class="lineno">   29</span>&#160;<span class="comment">// includes</span></div>
<div class="line"><a name="l00030"></a><span class="lineno">   30</span>&#160;<span class="preprocessor">#include &lt;NvInfer.h&gt;</span></div>
<div class="line"><a name="l00031"></a><span class="lineno">   31</span>&#160; </div>
<div class="line"><a name="l00032"></a><span class="lineno">   32</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="cudaUtility_8h.html">jetson-utils/cudaUtility.h</a>&gt;</span></div>
<div class="line"><a name="l00033"></a><span class="lineno">   33</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="commandLine_8h.html">jetson-utils/commandLine.h</a>&gt;</span></div>
<div class="line"><a name="l00034"></a><span class="lineno">   34</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="imageFormat_8h.html">jetson-utils/imageFormat.h</a>&gt;</span></div>
<div class="line"><a name="l00035"></a><span class="lineno">   35</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="timespec_8h.html">jetson-utils/timespec.h</a>&gt;</span></div>
<div class="line"><a name="l00036"></a><span class="lineno">   36</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="logging_8h.html">jetson-utils/logging.h</a>&gt;</span></div>
<div class="line"><a name="l00037"></a><span class="lineno">   37</span>&#160; </div>
<div class="line"><a name="l00038"></a><span class="lineno">   38</span>&#160;<span class="preprocessor">#include &lt;vector&gt;</span></div>
<div class="line"><a name="l00039"></a><span class="lineno">   39</span>&#160;<span class="preprocessor">#include &lt;sstream&gt;</span></div>
<div class="line"><a name="l00040"></a><span class="lineno">   40</span>&#160;<span class="preprocessor">#include &lt;math.h&gt;</span></div>
<div class="line"><a name="l00041"></a><span class="lineno">   41</span>&#160; </div>
<div class="line"><a name="l00042"></a><span class="lineno">   42</span>&#160; </div>
<div class="line"><a name="l00043"></a><span class="lineno">   43</span>&#160;<span class="preprocessor">#if NV_TENSORRT_MAJOR &gt;= 6</span></div>
<div class="line"><a name="l00044"></a><span class="lineno">   44</span>&#160;<span class="keyword">typedef</span> <a class="code" href="tensorNet_8h.html#a64c8f3dfeacfa962ff9e23c586aedd1b">nvinfer1::Dims3</a> <a class="code" href="tensorNet_8h.html#a64c8f3dfeacfa962ff9e23c586aedd1b">Dims3</a>;</div>
<div class="line"><a name="l00045"></a><span class="lineno">   45</span>&#160; </div>
<div class="line"><a name="l00046"></a><span class="lineno">   46</span>&#160;<span class="preprocessor">#define DIMS_C(x) x.d[0]</span></div>
<div class="line"><a name="l00047"></a><span class="lineno">   47</span>&#160;<span class="preprocessor">#define DIMS_H(x) x.d[1]</span></div>
<div class="line"><a name="l00048"></a><span class="lineno">   48</span>&#160;<span class="preprocessor">#define DIMS_W(x) x.d[2]</span></div>
<div class="line"><a name="l00049"></a><span class="lineno">   49</span>&#160; </div>
<div class="line"><a name="l00050"></a><span class="lineno">   50</span>&#160;<span class="preprocessor">#elif NV_TENSORRT_MAJOR &gt;= 2</span></div>
<div class="line"><a name="l00051"></a><span class="lineno">   51</span>&#160;<span class="keyword">typedef</span> nvinfer1::DimsCHW <a class="code" href="tensorNet_8h.html#a64c8f3dfeacfa962ff9e23c586aedd1b">Dims3</a>;</div>
<div class="line"><a name="l00052"></a><span class="lineno">   52</span>&#160; </div>
<div class="line"><a name="l00053"></a><span class="lineno">   53</span>&#160;<span class="preprocessor">#define DIMS_C(x) x.d[0]</span></div>
<div class="line"><a name="l00054"></a><span class="lineno">   54</span>&#160;<span class="preprocessor">#define DIMS_H(x) x.d[1]</span></div>
<div class="line"><a name="l00055"></a><span class="lineno">   55</span>&#160;<span class="preprocessor">#define DIMS_W(x) x.d[2]</span></div>
<div class="line"><a name="l00056"></a><span class="lineno">   56</span>&#160; </div>
<div class="line"><a name="l00057"></a><span class="lineno">   57</span>&#160;<span class="preprocessor">#else</span></div>
<div class="line"><a name="l00058"></a><span class="lineno"><a class="line" href="tensorNet_8h.html#a64c8f3dfeacfa962ff9e23c586aedd1b">   58</a></span>&#160;<span class="keyword">typedef</span> <a class="code" href="tensorNet_8h.html#a64c8f3dfeacfa962ff9e23c586aedd1b">nvinfer1::Dims3</a> <a class="code" href="tensorNet_8h.html#a64c8f3dfeacfa962ff9e23c586aedd1b">Dims3</a>; </div>
<div class="line"><a name="l00059"></a><span class="lineno">   59</span>&#160; </div>
<div class="line"><a name="l00060"></a><span class="lineno"><a class="line" href="tensorNet_8h.html#a2dd230b8ba7267356e52b308b5c40077">   60</a></span>&#160;<span class="preprocessor">#define DIMS_C(x) x.c</span></div>
<div class="line"><a name="l00061"></a><span class="lineno"><a class="line" href="tensorNet_8h.html#a1fc0b1785ea99bd75ec83b1eeb4e6120">   61</a></span>&#160;<span class="preprocessor">#define DIMS_H(x) x.h</span></div>
<div class="line"><a name="l00062"></a><span class="lineno"><a class="line" href="tensorNet_8h.html#a7d959cb65990da8bfea3d941d6daf416">   62</a></span>&#160;<span class="preprocessor">#define DIMS_W(x) x.w</span></div>
<div class="line"><a name="l00063"></a><span class="lineno">   63</span>&#160; </div>
<div class="line"><a name="l00064"></a><span class="lineno">   64</span>&#160;<span class="preprocessor">#ifndef NV_TENSORRT_MAJOR</span></div>
<div class="line"><a name="l00065"></a><span class="lineno"><a class="line" href="tensorNet_8h.html#aca5940a61fa51e91f41d88d9198bf935">   65</a></span>&#160;<span class="preprocessor">#define NV_TENSORRT_MAJOR 1</span></div>
<div class="line"><a name="l00066"></a><span class="lineno"><a class="line" href="tensorNet_8h.html#a7df0f049b87bee17d6aed394544e8979">   66</a></span>&#160;<span class="preprocessor">#define NV_TENSORRT_MINOR 0</span></div>
<div class="line"><a name="l00067"></a><span class="lineno">   67</span>&#160;<span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00068"></a><span class="lineno">   68</span>&#160;<span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00069"></a><span class="lineno">   69</span>&#160; </div>
<div class="line"><a name="l00070"></a><span class="lineno">   70</span>&#160;<span class="preprocessor">#if NV_TENSORRT_MAJOR &gt;= 8</span></div>
<div class="line"><a name="l00071"></a><span class="lineno">   71</span>&#160;<span class="preprocessor">#define NOEXCEPT noexcept</span></div>
<div class="line"><a name="l00072"></a><span class="lineno">   72</span>&#160;<span class="preprocessor">#else</span></div>
<div class="line"><a name="l00073"></a><span class="lineno"><a class="line" href="tensorNet_8h.html#a10a59554805ac7ce3905fd3540f98137">   73</a></span>&#160;<span class="preprocessor">#define NOEXCEPT</span></div>
<div class="line"><a name="l00074"></a><span class="lineno">   74</span>&#160;<span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00075"></a><span class="lineno">   75</span>&#160; </div>
<div class="line"><a name="l00076"></a><span class="lineno">   76</span>&#160; </div>
<div class="line"><a name="l00082"></a><span class="lineno"><a class="line" href="group__tensorNet.html#ga1d190b2948bf323a7c5f83fd3689c235">   82</a></span>&#160;<span class="preprocessor">#define TENSORRT_VERSION_CHECK(major, minor, patch)  (NV_TENSORRT_MAJOR &gt; major || (NV_TENSORRT_MAJOR == major &amp;&amp; NV_TENSORRT_MINOR &gt; minor) || (NV_TENSORRT_MAJOR == major &amp;&amp; NV_TENSORRT_MINOR == minor &amp;&amp; NV_TENSORRT_PATCH &gt;= patch))</span></div>
<div class="line"><a name="l00083"></a><span class="lineno">   83</span>&#160; </div>
<div class="line"><a name="l00088"></a><span class="lineno"><a class="line" href="group__tensorNet.html#ga5a46a965749d6118e01307fd4d4865c9">   88</a></span>&#160;<span class="preprocessor">#define DEFAULT_MAX_BATCH_SIZE  1</span></div>
<div class="line"><a name="l00089"></a><span class="lineno">   89</span>&#160; </div>
<div class="line"><a name="l00094"></a><span class="lineno"><a class="line" href="group__tensorNet.html#ga3c048e603c3c16fb810eb11c36242f82">   94</a></span>&#160;<span class="preprocessor">#define LOG_TRT &quot;[TRT]    &quot;</span></div>
<div class="line"><a name="l00095"></a><span class="lineno">   95</span>&#160; </div>
<div class="line"><a name="l00096"></a><span class="lineno">   96</span>&#160; </div>
<div class="line"><a name="l00102"></a><span class="lineno"><a class="line" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">  102</a></span>&#160;<span class="keyword">enum</span> <a class="code" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a></div>
<div class="line"><a name="l00103"></a><span class="lineno">  103</span>&#160;{</div>
<div class="line"><a name="l00104"></a><span class="lineno"><a class="line" href="group__tensorNet.html#ggaac6604fd52c6e5db82877390e0378623a1a4ed47814b2f80f0e92daad5af7bc38">  104</a></span>&#160;        <a class="code" href="group__tensorNet.html#ggaac6604fd52c6e5db82877390e0378623a1a4ed47814b2f80f0e92daad5af7bc38">TYPE_DISABLED</a> = 0,      </div>
<div class="line"><a name="l00105"></a><span class="lineno"><a class="line" href="group__tensorNet.html#ggaac6604fd52c6e5db82877390e0378623a1d325738f49e8e4c424ff671624e66f9">  105</a></span>&#160;        <a class="code" href="group__tensorNet.html#ggaac6604fd52c6e5db82877390e0378623a1d325738f49e8e4c424ff671624e66f9">TYPE_FASTEST</a>,           </div>
<div class="line"><a name="l00106"></a><span class="lineno"><a class="line" href="group__tensorNet.html#ggaac6604fd52c6e5db82877390e0378623a5bbefcad9ecb657a3841c2e8db6828d3">  106</a></span>&#160;        <a class="code" href="group__tensorNet.html#ggaac6604fd52c6e5db82877390e0378623a5bbefcad9ecb657a3841c2e8db6828d3">TYPE_FP32</a>,              </div>
<div class="line"><a name="l00107"></a><span class="lineno"><a class="line" href="group__tensorNet.html#ggaac6604fd52c6e5db82877390e0378623a085813e6021d0d8884d768725151a526">  107</a></span>&#160;        <a class="code" href="group__tensorNet.html#ggaac6604fd52c6e5db82877390e0378623a085813e6021d0d8884d768725151a526">TYPE_FP16</a>,              </div>
<div class="line"><a name="l00108"></a><span class="lineno"><a class="line" href="group__tensorNet.html#ggaac6604fd52c6e5db82877390e0378623a12cf69049b0ce2b80538213ab4ee4908">  108</a></span>&#160;        <a class="code" href="group__tensorNet.html#ggaac6604fd52c6e5db82877390e0378623a12cf69049b0ce2b80538213ab4ee4908">TYPE_INT8</a>,              </div>
<div class="line"><a name="l00109"></a><span class="lineno"><a class="line" href="group__tensorNet.html#ggaac6604fd52c6e5db82877390e0378623ad5386697191943144fa63df529e1a310">  109</a></span>&#160;        <a class="code" href="group__tensorNet.html#ggaac6604fd52c6e5db82877390e0378623ad5386697191943144fa63df529e1a310">NUM_PRECISIONS</a>          </div>
<div class="line"><a name="l00110"></a><span class="lineno">  110</span>&#160;};</div>
<div class="line"><a name="l00111"></a><span class="lineno">  111</span>&#160; </div>
<div class="line"><a name="l00116"></a><span class="lineno">  116</span>&#160;<span class="keyword">const</span> <span class="keywordtype">char</span>* <a class="code" href="group__tensorNet.html#ga1d1f73be994173912e9d964af1122ee1">precisionTypeToStr</a>( <a class="code" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a> type );</div>
<div class="line"><a name="l00117"></a><span class="lineno">  117</span>&#160; </div>
<div class="line"><a name="l00122"></a><span class="lineno">  122</span>&#160;<a class="code" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a> <a class="code" href="group__tensorNet.html#ga70317416490f79e0150e9c4f46444116">precisionTypeFromStr</a>( <span class="keyword">const</span> <span class="keywordtype">char</span>* str );</div>
<div class="line"><a name="l00123"></a><span class="lineno">  123</span>&#160; </div>
<div class="line"><a name="l00129"></a><span class="lineno"><a class="line" href="group__tensorNet.html#gaa5d3f9981cdbd91516c1474006a80fe4">  129</a></span>&#160;<span class="keyword">enum</span> <a class="code" href="group__tensorNet.html#gaa5d3f9981cdbd91516c1474006a80fe4">deviceType</a></div>
<div class="line"><a name="l00130"></a><span class="lineno">  130</span>&#160;{</div>
<div class="line"><a name="l00131"></a><span class="lineno"><a class="line" href="group__tensorNet.html#ggaa5d3f9981cdbd91516c1474006a80fe4adc7f3f88455afa81458863e5b3092e4b">  131</a></span>&#160;        <a class="code" href="group__tensorNet.html#ggaa5d3f9981cdbd91516c1474006a80fe4adc7f3f88455afa81458863e5b3092e4b">DEVICE_GPU</a> = 0,                 </div>
<div class="line"><a name="l00132"></a><span class="lineno"><a class="line" href="group__tensorNet.html#ggaa5d3f9981cdbd91516c1474006a80fe4aeaef16f066c95dd987fbde765b8b30b2">  132</a></span>&#160;        <a class="code" href="group__tensorNet.html#ggaa5d3f9981cdbd91516c1474006a80fe4aeaef16f066c95dd987fbde765b8b30b2">DEVICE_DLA</a>,                             </div>
<div class="line"><a name="l00133"></a><span class="lineno"><a class="line" href="group__tensorNet.html#ggaa5d3f9981cdbd91516c1474006a80fe4a4950aeb02ff7fba02eb2fd2437788399">  133</a></span>&#160;        <a class="code" href="group__tensorNet.html#ggaa5d3f9981cdbd91516c1474006a80fe4a4950aeb02ff7fba02eb2fd2437788399">DEVICE_DLA_0</a> = <a class="code" href="group__tensorNet.html#ggaa5d3f9981cdbd91516c1474006a80fe4aeaef16f066c95dd987fbde765b8b30b2">DEVICE_DLA</a>,      </div>
<div class="line"><a name="l00134"></a><span class="lineno"><a class="line" href="group__tensorNet.html#ggaa5d3f9981cdbd91516c1474006a80fe4a63fbbad29461776cf20c2137a3d124f0">  134</a></span>&#160;        <a class="code" href="group__tensorNet.html#ggaa5d3f9981cdbd91516c1474006a80fe4a63fbbad29461776cf20c2137a3d124f0">DEVICE_DLA_1</a>,                           </div>
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<div class="line"><a name="l00136"></a><span class="lineno">  136</span>&#160;};</div>
<div class="line"><a name="l00137"></a><span class="lineno">  137</span>&#160; </div>
<div class="line"><a name="l00142"></a><span class="lineno">  142</span>&#160;<span class="keyword">const</span> <span class="keywordtype">char</span>* <a class="code" href="group__tensorNet.html#ga85c110403b6c661b4a7042fc319f39b0">deviceTypeToStr</a>( <a class="code" href="group__tensorNet.html#gaa5d3f9981cdbd91516c1474006a80fe4">deviceType</a> type );</div>
<div class="line"><a name="l00143"></a><span class="lineno">  143</span>&#160; </div>
<div class="line"><a name="l00148"></a><span class="lineno">  148</span>&#160;<a class="code" href="group__tensorNet.html#gaa5d3f9981cdbd91516c1474006a80fe4">deviceType</a> <a class="code" href="group__tensorNet.html#ga35c5a50fb1ab97a827b18012534fd7a7">deviceTypeFromStr</a>( <span class="keyword">const</span> <span class="keywordtype">char</span>* str );</div>
<div class="line"><a name="l00149"></a><span class="lineno">  149</span>&#160; </div>
<div class="line"><a name="l00155"></a><span class="lineno"><a class="line" href="group__tensorNet.html#ga5d4597e0e7beae7133d542e220528725">  155</a></span>&#160;<span class="keyword">enum</span> <a class="code" href="group__tensorNet.html#ga5d4597e0e7beae7133d542e220528725">modelType</a></div>
<div class="line"><a name="l00156"></a><span class="lineno">  156</span>&#160;{</div>
<div class="line"><a name="l00157"></a><span class="lineno"><a class="line" href="group__tensorNet.html#gga5d4597e0e7beae7133d542e220528725aad94b3fe48299211488aae3c133721b1">  157</a></span>&#160;        <a class="code" href="group__tensorNet.html#gga5d4597e0e7beae7133d542e220528725aad94b3fe48299211488aae3c133721b1">MODEL_CUSTOM</a> = 0,       </div>
<div class="line"><a name="l00158"></a><span class="lineno"><a class="line" href="group__tensorNet.html#gga5d4597e0e7beae7133d542e220528725af850960ce09a0b0d4b38edef40e5d0e4">  158</a></span>&#160;        <a class="code" href="group__tensorNet.html#gga5d4597e0e7beae7133d542e220528725af850960ce09a0b0d4b38edef40e5d0e4">MODEL_CAFFE</a>,            </div>
<div class="line"><a name="l00159"></a><span class="lineno"><a class="line" href="group__tensorNet.html#gga5d4597e0e7beae7133d542e220528725a90e832c5673631bdfe24da7cd8eb52c9">  159</a></span>&#160;        <a class="code" href="group__tensorNet.html#gga5d4597e0e7beae7133d542e220528725a90e832c5673631bdfe24da7cd8eb52c9">MODEL_ONNX</a>,             </div>
<div class="line"><a name="l00160"></a><span class="lineno"><a class="line" href="group__tensorNet.html#gga5d4597e0e7beae7133d542e220528725ad8c909322673d53ee28de66aa57bcccd">  160</a></span>&#160;        <a class="code" href="group__tensorNet.html#gga5d4597e0e7beae7133d542e220528725ad8c909322673d53ee28de66aa57bcccd">MODEL_UFF</a>,              </div>
<div class="line"><a name="l00161"></a><span class="lineno"><a class="line" href="group__tensorNet.html#gga5d4597e0e7beae7133d542e220528725ad0f2ee11de0bfff76dace6976463556b">  161</a></span>&#160;        <a class="code" href="group__tensorNet.html#gga5d4597e0e7beae7133d542e220528725ad0f2ee11de0bfff76dace6976463556b">MODEL_ENGINE</a>            </div>
<div class="line"><a name="l00162"></a><span class="lineno">  162</span>&#160;};</div>
<div class="line"><a name="l00163"></a><span class="lineno">  163</span>&#160; </div>
<div class="line"><a name="l00168"></a><span class="lineno">  168</span>&#160;<span class="keyword">const</span> <span class="keywordtype">char</span>* <a class="code" href="group__tensorNet.html#gae771c047f44cc49238c00d0e8af48106">modelTypeToStr</a>( <a class="code" href="group__tensorNet.html#ga5d4597e0e7beae7133d542e220528725">modelType</a> type );</div>
<div class="line"><a name="l00169"></a><span class="lineno">  169</span>&#160; </div>
<div class="line"><a name="l00174"></a><span class="lineno">  174</span>&#160;<a class="code" href="group__tensorNet.html#ga5d4597e0e7beae7133d542e220528725">modelType</a> <a class="code" href="group__tensorNet.html#ga85f7b445f4341d24c65bb3bbc4a3204c">modelTypeFromStr</a>( <span class="keyword">const</span> <span class="keywordtype">char</span>* str );</div>
<div class="line"><a name="l00175"></a><span class="lineno">  175</span>&#160; </div>
<div class="line"><a name="l00180"></a><span class="lineno">  180</span>&#160;<a class="code" href="group__tensorNet.html#ga5d4597e0e7beae7133d542e220528725">modelType</a> <a class="code" href="group__tensorNet.html#ga675fb15bc5d4e2b8c4758c62adc6920d">modelTypeFromPath</a>( <span class="keyword">const</span> <span class="keywordtype">char</span>* path );</div>
<div class="line"><a name="l00181"></a><span class="lineno">  181</span>&#160; </div>
<div class="line"><a name="l00187"></a><span class="lineno"><a class="line" href="group__tensorNet.html#gae34d45c0faa674ef4cc0fbfc8fae5809">  187</a></span>&#160;<span class="keyword">enum</span> <a class="code" href="group__tensorNet.html#gae34d45c0faa674ef4cc0fbfc8fae5809">profilerQuery</a></div>
<div class="line"><a name="l00188"></a><span class="lineno">  188</span>&#160;{</div>
<div class="line"><a name="l00189"></a><span class="lineno"><a class="line" href="group__tensorNet.html#ggae34d45c0faa674ef4cc0fbfc8fae5809a7f84ee2f6773727f3b11408e8b2e150e">  189</a></span>&#160;        <a class="code" href="group__tensorNet.html#ggae34d45c0faa674ef4cc0fbfc8fae5809a7f84ee2f6773727f3b11408e8b2e150e">PROFILER_PREPROCESS</a> = 0,</div>
<div class="line"><a name="l00190"></a><span class="lineno"><a class="line" href="group__tensorNet.html#ggae34d45c0faa674ef4cc0fbfc8fae5809a624bb4adf22f078ad2804595dca02992">  190</a></span>&#160;        <a class="code" href="group__tensorNet.html#ggae34d45c0faa674ef4cc0fbfc8fae5809a624bb4adf22f078ad2804595dca02992">PROFILER_NETWORK</a>,</div>
<div class="line"><a name="l00191"></a><span class="lineno"><a class="line" href="group__tensorNet.html#ggae34d45c0faa674ef4cc0fbfc8fae5809a1fbcfa83e963d20d06f7c633bb2e4904">  191</a></span>&#160;        <a class="code" href="group__tensorNet.html#ggae34d45c0faa674ef4cc0fbfc8fae5809a1fbcfa83e963d20d06f7c633bb2e4904">PROFILER_POSTPROCESS</a>,</div>
<div class="line"><a name="l00192"></a><span class="lineno"><a class="line" href="group__tensorNet.html#ggae34d45c0faa674ef4cc0fbfc8fae5809a8cef88bc690e0a794987ade986169ee5">  192</a></span>&#160;        <a class="code" href="group__tensorNet.html#ggae34d45c0faa674ef4cc0fbfc8fae5809a8cef88bc690e0a794987ade986169ee5">PROFILER_VISUALIZE</a>,</div>
<div class="line"><a name="l00193"></a><span class="lineno"><a class="line" href="group__tensorNet.html#ggae34d45c0faa674ef4cc0fbfc8fae5809af9132edd0371e716aed4d46e3da5e9ea">  193</a></span>&#160;        <a class="code" href="group__tensorNet.html#ggae34d45c0faa674ef4cc0fbfc8fae5809af9132edd0371e716aed4d46e3da5e9ea">PROFILER_TOTAL</a>,</div>
<div class="line"><a name="l00194"></a><span class="lineno">  194</span>&#160;};</div>
<div class="line"><a name="l00195"></a><span class="lineno">  195</span>&#160; </div>
<div class="line"><a name="l00200"></a><span class="lineno">  200</span>&#160;<span class="keyword">const</span> <span class="keywordtype">char</span>* <a class="code" href="group__tensorNet.html#gaf219ba5ec806feca1433d20367e0f049">profilerQueryToStr</a>( <a class="code" href="group__tensorNet.html#gae34d45c0faa674ef4cc0fbfc8fae5809">profilerQuery</a> query );</div>
<div class="line"><a name="l00201"></a><span class="lineno">  201</span>&#160; </div>
<div class="line"><a name="l00206"></a><span class="lineno"><a class="line" href="group__tensorNet.html#gaaa4127ed22c7165a32d0474ebf97975e">  206</a></span>&#160;<span class="keyword">enum</span> <a class="code" href="group__tensorNet.html#gaaa4127ed22c7165a32d0474ebf97975e">profilerDevice</a></div>
<div class="line"><a name="l00207"></a><span class="lineno">  207</span>&#160;{</div>
<div class="line"><a name="l00208"></a><span class="lineno"><a class="line" href="group__tensorNet.html#ggaaa4127ed22c7165a32d0474ebf97975eaf33631f978127920224cd10c937e78d5">  208</a></span>&#160;        <a class="code" href="group__tensorNet.html#ggaaa4127ed22c7165a32d0474ebf97975eaf33631f978127920224cd10c937e78d5">PROFILER_CPU</a> = 0,       </div>
<div class="line"><a name="l00209"></a><span class="lineno"><a class="line" href="group__tensorNet.html#ggaaa4127ed22c7165a32d0474ebf97975eadbfd2a2033cd2a8df5fa51e13ff528b7">  209</a></span>&#160;        <a class="code" href="group__tensorNet.html#ggaaa4127ed22c7165a32d0474ebf97975eadbfd2a2033cd2a8df5fa51e13ff528b7">PROFILER_CUDA</a>,          </div>
<div class="line"><a name="l00210"></a><span class="lineno">  210</span>&#160;};</div>
<div class="line"><a name="l00211"></a><span class="lineno">  211</span>&#160; </div>
<div class="line"><a name="l00212"></a><span class="lineno">  212</span>&#160; </div>
<div class="line"><a name="l00218"></a><span class="lineno"><a class="line" href="group__tensorNet.html">  218</a></span>&#160;<span class="keyword">class </span><a class="code" href="group__tensorNet.html#classtensorNet">tensorNet</a></div>
<div class="line"><a name="l00219"></a><span class="lineno">  219</span>&#160;{</div>
<div class="line"><a name="l00220"></a><span class="lineno">  220</span>&#160;<span class="keyword">public</span>:</div>
<div class="line"><a name="l00224"></a><span class="lineno">  224</span>&#160;        <span class="keyword">virtual</span> <a class="code" href="group__tensorNet.html#ad19aafbfa262f9b8ffb0bff561f4d7f7">~tensorNet</a>();</div>
<div class="line"><a name="l00225"></a><span class="lineno">  225</span>&#160;        </div>
<div class="line"><a name="l00235"></a><span class="lineno">  235</span>&#160;        <span class="keywordtype">bool</span> <a class="code" href="group__tensorNet.html#a2e63d4670461814bd863ee0d9bd41526">LoadNetwork</a>( <span class="keyword">const</span> <span class="keywordtype">char</span>* prototxt, <span class="keyword">const</span> <span class="keywordtype">char</span>* model, <span class="keyword">const</span> <span class="keywordtype">char</span>* mean=NULL,</div>
<div class="line"><a name="l00236"></a><span class="lineno">  236</span>&#160;                                   <span class="keyword">const</span> <span class="keywordtype">char</span>* input_blob=<span class="stringliteral">&quot;data&quot;</span>, <span class="keyword">const</span> <span class="keywordtype">char</span>* output_blob=<span class="stringliteral">&quot;prob&quot;</span>,</div>
<div class="line"><a name="l00237"></a><span class="lineno">  237</span>&#160;                                   uint32_t maxBatchSize=<a class="code" href="group__tensorNet.html#ga5a46a965749d6118e01307fd4d4865c9">DEFAULT_MAX_BATCH_SIZE</a>, <a class="code" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a> precision=<a class="code" href="group__tensorNet.html#ggaac6604fd52c6e5db82877390e0378623a1d325738f49e8e4c424ff671624e66f9">TYPE_FASTEST</a>,</div>
<div class="line"><a name="l00238"></a><span class="lineno">  238</span>&#160;                                   <a class="code" href="group__tensorNet.html#gaa5d3f9981cdbd91516c1474006a80fe4">deviceType</a> device=<a class="code" href="group__tensorNet.html#ggaa5d3f9981cdbd91516c1474006a80fe4adc7f3f88455afa81458863e5b3092e4b">DEVICE_GPU</a>, <span class="keywordtype">bool</span> allowGPUFallback=<span class="keyword">true</span>,</div>
<div class="line"><a name="l00239"></a><span class="lineno">  239</span>&#160;                                   nvinfer1::IInt8Calibrator* calibrator=NULL, cudaStream_t stream=NULL );</div>
<div class="line"><a name="l00240"></a><span class="lineno">  240</span>&#160; </div>
<div class="line"><a name="l00250"></a><span class="lineno">  250</span>&#160;        <span class="keywordtype">bool</span> <a class="code" href="group__tensorNet.html#a2e63d4670461814bd863ee0d9bd41526">LoadNetwork</a>( <span class="keyword">const</span> <span class="keywordtype">char</span>* prototxt, <span class="keyword">const</span> <span class="keywordtype">char</span>* model, <span class="keyword">const</span> <span class="keywordtype">char</span>* mean,</div>
<div class="line"><a name="l00251"></a><span class="lineno">  251</span>&#160;                                   <span class="keyword">const</span> <span class="keywordtype">char</span>* input_blob, <span class="keyword">const</span> std::vector&lt;std::string&gt;&amp; output_blobs,</div>
<div class="line"><a name="l00252"></a><span class="lineno">  252</span>&#160;                                   uint32_t maxBatchSize=<a class="code" href="group__tensorNet.html#ga5a46a965749d6118e01307fd4d4865c9">DEFAULT_MAX_BATCH_SIZE</a>, <a class="code" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a> precision=<a class="code" href="group__tensorNet.html#ggaac6604fd52c6e5db82877390e0378623a1d325738f49e8e4c424ff671624e66f9">TYPE_FASTEST</a>,</div>
<div class="line"><a name="l00253"></a><span class="lineno">  253</span>&#160;                                   <a class="code" href="group__tensorNet.html#gaa5d3f9981cdbd91516c1474006a80fe4">deviceType</a> device=<a class="code" href="group__tensorNet.html#ggaa5d3f9981cdbd91516c1474006a80fe4adc7f3f88455afa81458863e5b3092e4b">DEVICE_GPU</a>, <span class="keywordtype">bool</span> allowGPUFallback=<span class="keyword">true</span>,</div>
<div class="line"><a name="l00254"></a><span class="lineno">  254</span>&#160;                                   nvinfer1::IInt8Calibrator* calibrator=NULL, cudaStream_t stream=NULL );</div>
<div class="line"><a name="l00255"></a><span class="lineno">  255</span>&#160; </div>
<div class="line"><a name="l00265"></a><span class="lineno">  265</span>&#160;        <span class="keywordtype">bool</span> <a class="code" href="group__tensorNet.html#a2e63d4670461814bd863ee0d9bd41526">LoadNetwork</a>( <span class="keyword">const</span> <span class="keywordtype">char</span>* prototxt, <span class="keyword">const</span> <span class="keywordtype">char</span>* model, <span class="keyword">const</span> <span class="keywordtype">char</span>* mean,</div>
<div class="line"><a name="l00266"></a><span class="lineno">  266</span>&#160;                                   <span class="keyword">const</span> std::vector&lt;std::string&gt;&amp; input_blobs, </div>
<div class="line"><a name="l00267"></a><span class="lineno">  267</span>&#160;                                   <span class="keyword">const</span> std::vector&lt;std::string&gt;&amp; output_blobs,</div>
<div class="line"><a name="l00268"></a><span class="lineno">  268</span>&#160;                                   uint32_t maxBatchSize=<a class="code" href="group__tensorNet.html#ga5a46a965749d6118e01307fd4d4865c9">DEFAULT_MAX_BATCH_SIZE</a>, </div>
<div class="line"><a name="l00269"></a><span class="lineno">  269</span>&#160;                                   <a class="code" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a> precision=<a class="code" href="group__tensorNet.html#ggaac6604fd52c6e5db82877390e0378623a1d325738f49e8e4c424ff671624e66f9">TYPE_FASTEST</a>,</div>
<div class="line"><a name="l00270"></a><span class="lineno">  270</span>&#160;                                   <a class="code" href="group__tensorNet.html#gaa5d3f9981cdbd91516c1474006a80fe4">deviceType</a> device=<a class="code" href="group__tensorNet.html#ggaa5d3f9981cdbd91516c1474006a80fe4adc7f3f88455afa81458863e5b3092e4b">DEVICE_GPU</a>, <span class="keywordtype">bool</span> allowGPUFallback=<span class="keyword">true</span>,</div>
<div class="line"><a name="l00271"></a><span class="lineno">  271</span>&#160;                                   nvinfer1::IInt8Calibrator* calibrator=NULL, cudaStream_t stream=NULL );</div>
<div class="line"><a name="l00272"></a><span class="lineno">  272</span>&#160; </div>
<div class="line"><a name="l00283"></a><span class="lineno">  283</span>&#160;        <span class="keywordtype">bool</span> <a class="code" href="group__tensorNet.html#a2e63d4670461814bd863ee0d9bd41526">LoadNetwork</a>( <span class="keyword">const</span> <span class="keywordtype">char</span>* prototxt, <span class="keyword">const</span> <span class="keywordtype">char</span>* model, <span class="keyword">const</span> <span class="keywordtype">char</span>* mean,</div>
<div class="line"><a name="l00284"></a><span class="lineno">  284</span>&#160;                                   <span class="keyword">const</span> <span class="keywordtype">char</span>* input_blob, <span class="keyword">const</span> <a class="code" href="tensorNet_8h.html#a64c8f3dfeacfa962ff9e23c586aedd1b">Dims3</a>&amp; input_dims, </div>
<div class="line"><a name="l00285"></a><span class="lineno">  285</span>&#160;                                   <span class="keyword">const</span> std::vector&lt;std::string&gt;&amp; output_blobs,</div>
<div class="line"><a name="l00286"></a><span class="lineno">  286</span>&#160;                                   uint32_t maxBatchSize=<a class="code" href="group__tensorNet.html#ga5a46a965749d6118e01307fd4d4865c9">DEFAULT_MAX_BATCH_SIZE</a>, </div>
<div class="line"><a name="l00287"></a><span class="lineno">  287</span>&#160;                                   <a class="code" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a> precision=<a class="code" href="group__tensorNet.html#ggaac6604fd52c6e5db82877390e0378623a1d325738f49e8e4c424ff671624e66f9">TYPE_FASTEST</a>,</div>
<div class="line"><a name="l00288"></a><span class="lineno">  288</span>&#160;                                   <a class="code" href="group__tensorNet.html#gaa5d3f9981cdbd91516c1474006a80fe4">deviceType</a> device=<a class="code" href="group__tensorNet.html#ggaa5d3f9981cdbd91516c1474006a80fe4adc7f3f88455afa81458863e5b3092e4b">DEVICE_GPU</a>, <span class="keywordtype">bool</span> allowGPUFallback=<span class="keyword">true</span>,</div>
<div class="line"><a name="l00289"></a><span class="lineno">  289</span>&#160;                                   nvinfer1::IInt8Calibrator* calibrator=NULL, cudaStream_t stream=NULL );</div>
<div class="line"><a name="l00290"></a><span class="lineno">  290</span>&#160; </div>
<div class="line"><a name="l00301"></a><span class="lineno">  301</span>&#160;        <span class="keywordtype">bool</span> <a class="code" href="group__tensorNet.html#a2e63d4670461814bd863ee0d9bd41526">LoadNetwork</a>( <span class="keyword">const</span> <span class="keywordtype">char</span>* prototxt, <span class="keyword">const</span> <span class="keywordtype">char</span>* model, <span class="keyword">const</span> <span class="keywordtype">char</span>* mean,</div>
<div class="line"><a name="l00302"></a><span class="lineno">  302</span>&#160;                                   <span class="keyword">const</span> std::vector&lt;std::string&gt;&amp; input_blobs, </div>
<div class="line"><a name="l00303"></a><span class="lineno">  303</span>&#160;                                   <span class="keyword">const</span> std::vector&lt;Dims3&gt;&amp; input_dims, </div>
<div class="line"><a name="l00304"></a><span class="lineno">  304</span>&#160;                                   <span class="keyword">const</span> std::vector&lt;std::string&gt;&amp; output_blobs,</div>
<div class="line"><a name="l00305"></a><span class="lineno">  305</span>&#160;                                   uint32_t maxBatchSize=<a class="code" href="group__tensorNet.html#ga5a46a965749d6118e01307fd4d4865c9">DEFAULT_MAX_BATCH_SIZE</a>, </div>
<div class="line"><a name="l00306"></a><span class="lineno">  306</span>&#160;                                   <a class="code" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a> precision=<a class="code" href="group__tensorNet.html#ggaac6604fd52c6e5db82877390e0378623a1d325738f49e8e4c424ff671624e66f9">TYPE_FASTEST</a>,</div>
<div class="line"><a name="l00307"></a><span class="lineno">  307</span>&#160;                                   <a class="code" href="group__tensorNet.html#gaa5d3f9981cdbd91516c1474006a80fe4">deviceType</a> device=<a class="code" href="group__tensorNet.html#ggaa5d3f9981cdbd91516c1474006a80fe4adc7f3f88455afa81458863e5b3092e4b">DEVICE_GPU</a>, <span class="keywordtype">bool</span> allowGPUFallback=<span class="keyword">true</span>,</div>
<div class="line"><a name="l00308"></a><span class="lineno">  308</span>&#160;                                   nvinfer1::IInt8Calibrator* calibrator=NULL, cudaStream_t stream=NULL );</div>
<div class="line"><a name="l00309"></a><span class="lineno">  309</span>&#160; </div>
<div class="line"><a name="l00316"></a><span class="lineno">  316</span>&#160;        <span class="keywordtype">bool</span> <a class="code" href="group__tensorNet.html#acb8076f6ab8d13b6507140826cf438d8">LoadEngine</a>( <span class="keyword">const</span> <span class="keywordtype">char</span>* engine_filename,</div>
<div class="line"><a name="l00317"></a><span class="lineno">  317</span>&#160;                                  <span class="keyword">const</span> std::vector&lt;std::string&gt;&amp; input_blobs, </div>
<div class="line"><a name="l00318"></a><span class="lineno">  318</span>&#160;                                  <span class="keyword">const</span> std::vector&lt;std::string&gt;&amp; output_blobs,</div>
<div class="line"><a name="l00319"></a><span class="lineno">  319</span>&#160;                                  nvinfer1::IPluginFactory* pluginFactory=NULL,</div>
<div class="line"><a name="l00320"></a><span class="lineno">  320</span>&#160;                                  <a class="code" href="group__tensorNet.html#gaa5d3f9981cdbd91516c1474006a80fe4">deviceType</a> device=<a class="code" href="group__tensorNet.html#ggaa5d3f9981cdbd91516c1474006a80fe4adc7f3f88455afa81458863e5b3092e4b">DEVICE_GPU</a>,</div>
<div class="line"><a name="l00321"></a><span class="lineno">  321</span>&#160;                                  cudaStream_t stream=NULL );</div>
<div class="line"><a name="l00322"></a><span class="lineno">  322</span>&#160; </div>
<div class="line"><a name="l00330"></a><span class="lineno">  330</span>&#160;        <span class="keywordtype">bool</span> <a class="code" href="group__tensorNet.html#acb8076f6ab8d13b6507140826cf438d8">LoadEngine</a>( <span class="keywordtype">char</span>* engine_stream, <span class="keywordtype">size_t</span> engine_size,</div>
<div class="line"><a name="l00331"></a><span class="lineno">  331</span>&#160;                                  <span class="keyword">const</span> std::vector&lt;std::string&gt;&amp; input_blobs, </div>
<div class="line"><a name="l00332"></a><span class="lineno">  332</span>&#160;                                  <span class="keyword">const</span> std::vector&lt;std::string&gt;&amp; output_blobs,</div>
<div class="line"><a name="l00333"></a><span class="lineno">  333</span>&#160;                                  nvinfer1::IPluginFactory* pluginFactory=NULL,</div>
<div class="line"><a name="l00334"></a><span class="lineno">  334</span>&#160;                                  <a class="code" href="group__tensorNet.html#gaa5d3f9981cdbd91516c1474006a80fe4">deviceType</a> device=<a class="code" href="group__tensorNet.html#ggaa5d3f9981cdbd91516c1474006a80fe4adc7f3f88455afa81458863e5b3092e4b">DEVICE_GPU</a>,</div>
<div class="line"><a name="l00335"></a><span class="lineno">  335</span>&#160;                                  cudaStream_t stream=NULL );</div>
<div class="line"><a name="l00336"></a><span class="lineno">  336</span>&#160; </div>
<div class="line"><a name="l00344"></a><span class="lineno">  344</span>&#160;        <span class="keywordtype">bool</span> <a class="code" href="group__tensorNet.html#acb8076f6ab8d13b6507140826cf438d8">LoadEngine</a>( nvinfer1::ICudaEngine* engine,</div>
<div class="line"><a name="l00345"></a><span class="lineno">  345</span>&#160;                                  <span class="keyword">const</span> std::vector&lt;std::string&gt;&amp; input_blobs, </div>
<div class="line"><a name="l00346"></a><span class="lineno">  346</span>&#160;                                  <span class="keyword">const</span> std::vector&lt;std::string&gt;&amp; output_blobs,</div>
<div class="line"><a name="l00347"></a><span class="lineno">  347</span>&#160;                                  <a class="code" href="group__tensorNet.html#gaa5d3f9981cdbd91516c1474006a80fe4">deviceType</a> device=<a class="code" href="group__tensorNet.html#ggaa5d3f9981cdbd91516c1474006a80fe4adc7f3f88455afa81458863e5b3092e4b">DEVICE_GPU</a>,</div>
<div class="line"><a name="l00348"></a><span class="lineno">  348</span>&#160;                                  cudaStream_t stream=NULL );</div>
<div class="line"><a name="l00349"></a><span class="lineno">  349</span>&#160; </div>
<div class="line"><a name="l00353"></a><span class="lineno">  353</span>&#160;        <span class="keywordtype">bool</span> <a class="code" href="group__tensorNet.html#acb8076f6ab8d13b6507140826cf438d8">LoadEngine</a>( <span class="keyword">const</span> <span class="keywordtype">char</span>* filename, <span class="keywordtype">char</span>** stream, <span class="keywordtype">size_t</span>* size );</div>
<div class="line"><a name="l00354"></a><span class="lineno">  354</span>&#160; </div>
<div class="line"><a name="l00360"></a><span class="lineno">  360</span>&#160;        <span class="keyword">static</span> <span class="keywordtype">bool</span> <a class="code" href="group__tensorNet.html#a57cacfea82e9329c2cf776837dd00aef">LoadClassLabels</a>( <span class="keyword">const</span> <span class="keywordtype">char</span>* filename, std::vector&lt;std::string&gt;&amp; descriptions, <span class="keywordtype">int</span> expectedClasses=-1 );</div>
<div class="line"><a name="l00361"></a><span class="lineno">  361</span>&#160; </div>
<div class="line"><a name="l00367"></a><span class="lineno">  367</span>&#160;        <span class="keyword">static</span> <span class="keywordtype">bool</span> <a class="code" href="group__tensorNet.html#a57cacfea82e9329c2cf776837dd00aef">LoadClassLabels</a>( <span class="keyword">const</span> <span class="keywordtype">char</span>* filename, std::vector&lt;std::string&gt;&amp; descriptions, std::vector&lt;std::string&gt;&amp; synsets, <span class="keywordtype">int</span> expectedClasses=-1 );</div>
<div class="line"><a name="l00368"></a><span class="lineno">  368</span>&#160; </div>
<div class="line"><a name="l00374"></a><span class="lineno">  374</span>&#160;        <span class="keyword">static</span> <span class="keywordtype">bool</span> <a class="code" href="group__tensorNet.html#a7b87410f9133aea37b46979d543219b9">LoadClassColors</a>( <span class="keyword">const</span> <span class="keywordtype">char</span>* filename, float4* colors, <span class="keywordtype">int</span> expectedClasses, <span class="keywordtype">float</span> defaultAlpha=255.0f );</div>
<div class="line"><a name="l00375"></a><span class="lineno">  375</span>&#160; </div>
<div class="line"><a name="l00381"></a><span class="lineno">  381</span>&#160;        <span class="keyword">static</span> <span class="keywordtype">bool</span> <a class="code" href="group__tensorNet.html#a7b87410f9133aea37b46979d543219b9">LoadClassColors</a>( <span class="keyword">const</span> <span class="keywordtype">char</span>* filename, float4** colors, <span class="keywordtype">int</span> expectedClasses, <span class="keywordtype">float</span> defaultAlpha=255.0f );</div>
<div class="line"><a name="l00382"></a><span class="lineno">  382</span>&#160; </div>
<div class="line"><a name="l00387"></a><span class="lineno">  387</span>&#160;        <span class="keyword">static</span> float4 <a class="code" href="group__tensorNet.html#a4fe18908c74efda1708029ca3b04f0e8">GenerateColor</a>( uint32_t <a class="code" href="cudaPointCloud_8h.html#ad9bd89745d72dbc52651f62814eed36d">classID</a>, <span class="keywordtype">float</span> <a class="code" href="cudaVector_8h.html#aa94774faf063d34dab6f3f374d73ea7a">alpha</a>=255.0f ); </div>
<div class="line"><a name="l00388"></a><span class="lineno">  388</span>&#160;        </div>
<div class="line"><a name="l00392"></a><span class="lineno">  392</span>&#160;        <span class="keywordtype">void</span> <a class="code" href="group__tensorNet.html#a3413eb0ad4f240f457f192f39e2e03e8">EnableLayerProfiler</a>();</div>
<div class="line"><a name="l00393"></a><span class="lineno">  393</span>&#160; </div>
<div class="line"><a name="l00397"></a><span class="lineno">  397</span>&#160;        <span class="keywordtype">void</span> <a class="code" href="group__tensorNet.html#ae49f74ff83e46112a30318fa0576cace">EnableDebug</a>();</div>
<div class="line"><a name="l00398"></a><span class="lineno">  398</span>&#160; </div>
<div class="line"><a name="l00402"></a><span class="lineno"><a class="line" href="group__tensorNet.html#a7d0ec0d8504ac8b26c5ab4a6136599ca">  402</a></span>&#160;        <span class="keyword">inline</span> <span class="keywordtype">bool</span> <a class="code" href="group__tensorNet.html#a7d0ec0d8504ac8b26c5ab4a6136599ca">AllowGPUFallback</a>()<span class="keyword"> const                                    </span>{ <span class="keywordflow">return</span> <a class="code" href="group__tensorNet.html#a8e7b5913f3f54d4bb0e6aa8e6071a74a">mAllowGPUFallback</a>; }</div>
<div class="line"><a name="l00403"></a><span class="lineno">  403</span>&#160; </div>
<div class="line"><a name="l00407"></a><span class="lineno"><a class="line" href="group__tensorNet.html#a92bb737172d26bda5f67d15346a02514">  407</a></span>&#160;        <span class="keyword">inline</span> <a class="code" href="group__tensorNet.html#gaa5d3f9981cdbd91516c1474006a80fe4">deviceType</a> <a class="code" href="group__tensorNet.html#a92bb737172d26bda5f67d15346a02514">GetDevice</a>()<span class="keyword"> const                                     </span>{ <span class="keywordflow">return</span> <a class="code" href="group__tensorNet.html#a2f14a2f4a4dfbb51b80f80a2e47a695c">mDevice</a>; }</div>
<div class="line"><a name="l00408"></a><span class="lineno">  408</span>&#160; </div>
<div class="line"><a name="l00412"></a><span class="lineno"><a class="line" href="group__tensorNet.html#afb38b5f171025e987a00214cc4379ca9">  412</a></span>&#160;        <span class="keyword">inline</span> <a class="code" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a> <a class="code" href="group__tensorNet.html#afb38b5f171025e987a00214cc4379ca9">GetPrecision</a>()<span class="keyword"> const                               </span>{ <span class="keywordflow">return</span> <a class="code" href="group__tensorNet.html#a164c1dcf9dcbc085c1b421855eda665f">mPrecision</a>; }</div>
<div class="line"><a name="l00413"></a><span class="lineno">  413</span>&#160; </div>
<div class="line"><a name="l00417"></a><span class="lineno"><a class="line" href="group__tensorNet.html#a6b8e8dba05bc5c677027913d8c64f259">  417</a></span>&#160;        <span class="keyword">inline</span> <span class="keywordtype">bool</span> <a class="code" href="group__tensorNet.html#a6b8e8dba05bc5c677027913d8c64f259">IsPrecision</a>( <a class="code" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a> type )<span class="keyword"> const             </span>{ <span class="keywordflow">return</span> (<a class="code" href="group__tensorNet.html#a164c1dcf9dcbc085c1b421855eda665f">mPrecision</a> == type); }</div>
<div class="line"><a name="l00418"></a><span class="lineno">  418</span>&#160; </div>
<div class="line"><a name="l00422"></a><span class="lineno">  422</span>&#160;        <span class="keyword">static</span> <a class="code" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a> <a class="code" href="group__tensorNet.html#a3c0509631176be6f9e25673cb0aa12dc">SelectPrecision</a>( <a class="code" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a> precision, <a class="code" href="group__tensorNet.html#gaa5d3f9981cdbd91516c1474006a80fe4">deviceType</a> device=<a class="code" href="group__tensorNet.html#ggaa5d3f9981cdbd91516c1474006a80fe4adc7f3f88455afa81458863e5b3092e4b">DEVICE_GPU</a>, <span class="keywordtype">bool</span> allowInt8=<span class="keyword">true</span> );</div>
<div class="line"><a name="l00423"></a><span class="lineno">  423</span>&#160; </div>
<div class="line"><a name="l00427"></a><span class="lineno">  427</span>&#160;        <span class="keyword">static</span> <a class="code" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a> <a class="code" href="group__tensorNet.html#abe33fae5332296e2d917cb4ce435e255">FindFastestPrecision</a>( <a class="code" href="group__tensorNet.html#gaa5d3f9981cdbd91516c1474006a80fe4">deviceType</a> device=<a class="code" href="group__tensorNet.html#ggaa5d3f9981cdbd91516c1474006a80fe4adc7f3f88455afa81458863e5b3092e4b">DEVICE_GPU</a>, <span class="keywordtype">bool</span> allowInt8=<span class="keyword">true</span> );</div>
<div class="line"><a name="l00428"></a><span class="lineno">  428</span>&#160; </div>
<div class="line"><a name="l00432"></a><span class="lineno">  432</span>&#160;        <span class="keyword">static</span> std::vector&lt;precisionType&gt; <a class="code" href="group__tensorNet.html#ae88436e652afdd7bceef7cb7c5fde7a6">DetectNativePrecisions</a>( <a class="code" href="group__tensorNet.html#gaa5d3f9981cdbd91516c1474006a80fe4">deviceType</a> device=<a class="code" href="group__tensorNet.html#ggaa5d3f9981cdbd91516c1474006a80fe4adc7f3f88455afa81458863e5b3092e4b">DEVICE_GPU</a> );</div>
<div class="line"><a name="l00433"></a><span class="lineno">  433</span>&#160;        </div>
<div class="line"><a name="l00437"></a><span class="lineno">  437</span>&#160;        <span class="keyword">static</span> <span class="keywordtype">bool</span> <a class="code" href="group__tensorNet.html#aa3bf1a3bf1fca38b39a200b4d8f727b2">DetectNativePrecision</a>( <span class="keyword">const</span> std::vector&lt;precisionType&gt;&amp; nativeTypes, <a class="code" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a> type );</div>
<div class="line"><a name="l00438"></a><span class="lineno">  438</span>&#160; </div>
<div class="line"><a name="l00442"></a><span class="lineno">  442</span>&#160;        <span class="keyword">static</span> <span class="keywordtype">bool</span> <a class="code" href="group__tensorNet.html#aa3bf1a3bf1fca38b39a200b4d8f727b2">DetectNativePrecision</a>( <a class="code" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a> precision, <a class="code" href="group__tensorNet.html#gaa5d3f9981cdbd91516c1474006a80fe4">deviceType</a> device=<a class="code" href="group__tensorNet.html#ggaa5d3f9981cdbd91516c1474006a80fe4adc7f3f88455afa81458863e5b3092e4b">DEVICE_GPU</a> );</div>
<div class="line"><a name="l00443"></a><span class="lineno">  443</span>&#160; </div>
<div class="line"><a name="l00447"></a><span class="lineno"><a class="line" href="group__tensorNet.html#a34e350ec6185277ac09ae55a79403e62">  447</a></span>&#160;        <span class="keyword">inline</span> cudaStream_t <a class="code" href="group__tensorNet.html#a34e350ec6185277ac09ae55a79403e62">GetStream</a>()<span class="keyword"> const                                   </span>{ <span class="keywordflow">return</span> <a class="code" href="group__tensorNet.html#a1ed6e418a135650c7cf91498379727ae">mStream</a>; }</div>
<div class="line"><a name="l00448"></a><span class="lineno">  448</span>&#160; </div>
<div class="line"><a name="l00452"></a><span class="lineno">  452</span>&#160;        cudaStream_t <a class="code" href="group__tensorNet.html#a78cecfb7505be0ea59d29041abc85cbb">CreateStream</a>( <span class="keywordtype">bool</span> nonBlocking=<span class="keyword">true</span> );</div>
<div class="line"><a name="l00453"></a><span class="lineno">  453</span>&#160; </div>
<div class="line"><a name="l00457"></a><span class="lineno">  457</span>&#160;        <span class="keywordtype">void</span> <a class="code" href="group__tensorNet.html#a679b177784c85bfdba63dcd1008ff633">SetStream</a>( cudaStream_t stream );</div>
<div class="line"><a name="l00458"></a><span class="lineno">  458</span>&#160; </div>
<div class="line"><a name="l00462"></a><span class="lineno"><a class="line" href="group__tensorNet.html#a624881afe27acd2b2fff0f0f75308ea2">  462</a></span>&#160;        <span class="keyword">inline</span> <span class="keyword">const</span> <span class="keywordtype">char</span>* <a class="code" href="group__tensorNet.html#a624881afe27acd2b2fff0f0f75308ea2">GetPrototxtPath</a>()<span class="keyword"> const                              </span>{ <span class="keywordflow">return</span> <a class="code" href="group__tensorNet.html#a54005b86b851fa71aeb7a83d4ad32362">mPrototxtPath</a>.c_str(); }</div>
<div class="line"><a name="l00463"></a><span class="lineno">  463</span>&#160; </div>
<div class="line"><a name="l00467"></a><span class="lineno"><a class="line" href="group__tensorNet.html#ac74d7f0571b7782b945ff85fd6894044">  467</a></span>&#160;        <span class="keyword">inline</span> <span class="keyword">const</span> <span class="keywordtype">char</span>* <a class="code" href="group__tensorNet.html#ac74d7f0571b7782b945ff85fd6894044">GetModelPath</a>()<span class="keyword"> const                                 </span>{ <span class="keywordflow">return</span> <a class="code" href="group__tensorNet.html#a7cb91e06b296431680d20e7e9fb0187d">mModelPath</a>.c_str(); }</div>
<div class="line"><a name="l00468"></a><span class="lineno">  468</span>&#160; </div>
<div class="line"><a name="l00472"></a><span class="lineno"><a class="line" href="group__tensorNet.html#a03252bed041613fc1afb9d3cbb99663d">  472</a></span>&#160;        <span class="keyword">inline</span> <span class="keyword">const</span> <span class="keywordtype">char</span>* <a class="code" href="group__tensorNet.html#a03252bed041613fc1afb9d3cbb99663d">GetModelFilename</a>()<span class="keyword"> const                             </span>{ <span class="keywordflow">return</span> <a class="code" href="group__tensorNet.html#a338246dc13b84166ee5ea917d84379aa">mModelFile</a>.c_str(); }</div>
<div class="line"><a name="l00473"></a><span class="lineno">  473</span>&#160;        </div>
<div class="line"><a name="l00477"></a><span class="lineno"><a class="line" href="group__tensorNet.html#acfa7f1f01b46f658ffc96f8a002e8d48">  477</a></span>&#160;        <span class="keyword">inline</span> <a class="code" href="group__tensorNet.html#ga5d4597e0e7beae7133d542e220528725">modelType</a> <a class="code" href="group__tensorNet.html#acfa7f1f01b46f658ffc96f8a002e8d48">GetModelType</a>()<span class="keyword"> const                                   </span>{ <span class="keywordflow">return</span> <a class="code" href="group__tensorNet.html#ab5c88cf4590b53804ebedaa292d1402c">mModelType</a>; }</div>
<div class="line"><a name="l00478"></a><span class="lineno">  478</span>&#160; </div>
<div class="line"><a name="l00482"></a><span class="lineno"><a class="line" href="group__tensorNet.html#a0a09d691ea080bd9734c5782c8fff6fd">  482</a></span>&#160;        <span class="keyword">inline</span> <span class="keywordtype">bool</span> <a class="code" href="group__tensorNet.html#a0a09d691ea080bd9734c5782c8fff6fd">IsModelType</a>( <a class="code" href="group__tensorNet.html#ga5d4597e0e7beae7133d542e220528725">modelType</a> type )<span class="keyword"> const                 </span>{ <span class="keywordflow">return</span> (<a class="code" href="group__tensorNet.html#ab5c88cf4590b53804ebedaa292d1402c">mModelType</a> == type); }</div>
<div class="line"><a name="l00483"></a><span class="lineno">  483</span>&#160; </div>
<div class="line"><a name="l00487"></a><span class="lineno"><a class="line" href="group__tensorNet.html#ac583b8de1dd64b47338b4a3eb42ac166">  487</a></span>&#160;        <span class="keyword">inline</span> uint32_t <a class="code" href="group__tensorNet.html#ac583b8de1dd64b47338b4a3eb42ac166">GetInputLayers</a>()<span class="keyword"> const                                  </span>{ <span class="keywordflow">return</span> <a class="code" href="group__tensorNet.html#a939a5123396b35a0dbee8d094d881d62">mInputs</a>.size(); }</div>
<div class="line"><a name="l00488"></a><span class="lineno">  488</span>&#160; </div>
<div class="line"><a name="l00492"></a><span class="lineno"><a class="line" href="group__tensorNet.html#a2dcc770a7215e2e76a8d520a36689e16">  492</a></span>&#160;        <span class="keyword">inline</span> uint32_t <a class="code" href="group__tensorNet.html#a2dcc770a7215e2e76a8d520a36689e16">GetOutputLayers</a>()<span class="keyword"> const                                 </span>{ <span class="keywordflow">return</span> <a class="code" href="group__tensorNet.html#afcdbdb26dc6e5117f867c83e635a0250">mOutputs</a>.size(); }</div>
<div class="line"><a name="l00493"></a><span class="lineno">  493</span>&#160; </div>
<div class="line"><a name="l00497"></a><span class="lineno"><a class="line" href="group__tensorNet.html#adcfe61596f291e75a87d36c3771f25df">  497</a></span>&#160;        <span class="keyword">inline</span> <a class="code" href="tensorNet_8h.html#a64c8f3dfeacfa962ff9e23c586aedd1b">Dims3</a> <a class="code" href="group__tensorNet.html#adcfe61596f291e75a87d36c3771f25df">GetInputDims</a>( uint32_t layer=0 )<span class="keyword"> const             </span>{ <span class="keywordflow">return</span> <a class="code" href="group__tensorNet.html#a939a5123396b35a0dbee8d094d881d62">mInputs</a>[layer].dims; }</div>
<div class="line"><a name="l00498"></a><span class="lineno">  498</span>&#160; </div>
<div class="line"><a name="l00502"></a><span class="lineno"><a class="line" href="group__tensorNet.html#a2d75ef6f579d1a71ff472bfafd0b7795">  502</a></span>&#160;        <span class="keyword">inline</span> uint32_t <a class="code" href="group__tensorNet.html#a2d75ef6f579d1a71ff472bfafd0b7795">GetInputWidth</a>( uint32_t layer=0 )<span class="keyword"> const </span>{ <span class="keywordflow">return</span> <a class="code" href="tensorNet_8h.html#a7d959cb65990da8bfea3d941d6daf416">DIMS_W</a>(<a class="code" href="group__tensorNet.html#a939a5123396b35a0dbee8d094d881d62">mInputs</a>[layer].dims); }</div>
<div class="line"><a name="l00503"></a><span class="lineno">  503</span>&#160; </div>
<div class="line"><a name="l00507"></a><span class="lineno"><a class="line" href="group__tensorNet.html#a214a92c41dcdcb58b3cd8496aac0857a">  507</a></span>&#160;        <span class="keyword">inline</span> uint32_t <a class="code" href="group__tensorNet.html#a214a92c41dcdcb58b3cd8496aac0857a">GetInputHeight</a>( uint32_t layer=0 )<span class="keyword"> const        </span>{ <span class="keywordflow">return</span> <a class="code" href="tensorNet_8h.html#a1fc0b1785ea99bd75ec83b1eeb4e6120">DIMS_H</a>(<a class="code" href="group__tensorNet.html#a939a5123396b35a0dbee8d094d881d62">mInputs</a>[layer].dims); }</div>
<div class="line"><a name="l00508"></a><span class="lineno">  508</span>&#160; </div>
<div class="line"><a name="l00512"></a><span class="lineno"><a class="line" href="group__tensorNet.html#a2c80d46f8a01335e77e41023544102c9">  512</a></span>&#160;        <span class="keyword">inline</span> uint32_t <a class="code" href="group__tensorNet.html#a2c80d46f8a01335e77e41023544102c9">GetInputSize</a>( uint32_t layer=0 )<span class="keyword"> const          </span>{ <span class="keywordflow">return</span> <a class="code" href="group__tensorNet.html#a939a5123396b35a0dbee8d094d881d62">mInputs</a>[layer].size; }</div>
<div class="line"><a name="l00513"></a><span class="lineno">  513</span>&#160; </div>
<div class="line"><a name="l00517"></a><span class="lineno"><a class="line" href="group__tensorNet.html#a3a8851513971d11746231d217f57b69f">  517</a></span>&#160;        <span class="keyword">inline</span> <span class="keywordtype">float</span>* <a class="code" href="group__tensorNet.html#a3a8851513971d11746231d217f57b69f">GetInputPtr</a>( uint32_t layer=0 )<span class="keyword"> const             </span>{ <span class="keywordflow">return</span> <a class="code" href="group__tensorNet.html#a939a5123396b35a0dbee8d094d881d62">mInputs</a>[layer].CUDA; }</div>
<div class="line"><a name="l00518"></a><span class="lineno">  518</span>&#160;        </div>
<div class="line"><a name="l00522"></a><span class="lineno"><a class="line" href="group__tensorNet.html#a77703f2a7b59f836c93ae28811e22cb0">  522</a></span>&#160;        <span class="keyword">inline</span> <a class="code" href="tensorNet_8h.html#a64c8f3dfeacfa962ff9e23c586aedd1b">Dims3</a> <a class="code" href="group__tensorNet.html#a77703f2a7b59f836c93ae28811e22cb0">GetOutputDims</a>( uint32_t layer=0 )<span class="keyword"> const            </span>{ <span class="keywordflow">return</span> <a class="code" href="group__tensorNet.html#afcdbdb26dc6e5117f867c83e635a0250">mOutputs</a>[layer].dims; }</div>
<div class="line"><a name="l00523"></a><span class="lineno">  523</span>&#160; </div>
<div class="line"><a name="l00527"></a><span class="lineno"><a class="line" href="group__tensorNet.html#a09d63a8fd906c99f8158bf9460a83c02">  527</a></span>&#160;        <span class="keyword">inline</span> uint32_t <a class="code" href="group__tensorNet.html#a09d63a8fd906c99f8158bf9460a83c02">GetOutputWidth</a>( uint32_t layer=0 )<span class="keyword"> const        </span>{ <span class="keywordflow">return</span> <a class="code" href="tensorNet_8h.html#a7d959cb65990da8bfea3d941d6daf416">DIMS_W</a>(<a class="code" href="group__tensorNet.html#afcdbdb26dc6e5117f867c83e635a0250">mOutputs</a>[layer].dims); }</div>
<div class="line"><a name="l00528"></a><span class="lineno">  528</span>&#160; </div>
<div class="line"><a name="l00532"></a><span class="lineno"><a class="line" href="group__tensorNet.html#a613679e8ee5315f3b5b16a39011ba76e">  532</a></span>&#160;        <span class="keyword">inline</span> uint32_t <a class="code" href="group__tensorNet.html#a613679e8ee5315f3b5b16a39011ba76e">GetOutputHeight</a>( uint32_t layer=0 )<span class="keyword"> const       </span>{ <span class="keywordflow">return</span> <a class="code" href="tensorNet_8h.html#a1fc0b1785ea99bd75ec83b1eeb4e6120">DIMS_H</a>(<a class="code" href="group__tensorNet.html#afcdbdb26dc6e5117f867c83e635a0250">mOutputs</a>[layer].dims); }</div>
<div class="line"><a name="l00533"></a><span class="lineno">  533</span>&#160; </div>
<div class="line"><a name="l00537"></a><span class="lineno"><a class="line" href="group__tensorNet.html#ae1486438dcdbe0d7f5e88e5336a42efa">  537</a></span>&#160;        <span class="keyword">inline</span> uint32_t <a class="code" href="group__tensorNet.html#ae1486438dcdbe0d7f5e88e5336a42efa">GetOutputSize</a>( uint32_t layer=0 )<span class="keyword"> const </span>{ <span class="keywordflow">return</span> <a class="code" href="group__tensorNet.html#afcdbdb26dc6e5117f867c83e635a0250">mOutputs</a>[layer].size; }</div>
<div class="line"><a name="l00538"></a><span class="lineno">  538</span>&#160; </div>
<div class="line"><a name="l00542"></a><span class="lineno"><a class="line" href="group__tensorNet.html#a2e5a4207d90828c31255846b11a431ea">  542</a></span>&#160;        <span class="keyword">inline</span> <span class="keywordtype">float</span>* <a class="code" href="group__tensorNet.html#a2e5a4207d90828c31255846b11a431ea">GetOutputPtr</a>( uint32_t layer=0 )<span class="keyword"> const            </span>{ <span class="keywordflow">return</span> <a class="code" href="group__tensorNet.html#afcdbdb26dc6e5117f867c83e635a0250">mOutputs</a>[layer].CUDA; }</div>
<div class="line"><a name="l00543"></a><span class="lineno">  543</span>&#160;        </div>
<div class="line"><a name="l00547"></a><span class="lineno"><a class="line" href="group__tensorNet.html#a9dd2db089176ae6878e9ea7dd8fd80c3">  547</a></span>&#160;        <span class="keyword">inline</span> <span class="keywordtype">float</span> <a class="code" href="group__tensorNet.html#a9dd2db089176ae6878e9ea7dd8fd80c3">GetNetworkFPS</a>()                                                    { <span class="keywordflow">return</span> 1000.0f / <a class="code" href="group__tensorNet.html#a49faef5920860345e503023b7c84423c">GetNetworkTime</a>(); }</div>
<div class="line"><a name="l00548"></a><span class="lineno">  548</span>&#160; </div>
<div class="line"><a name="l00552"></a><span class="lineno"><a class="line" href="group__tensorNet.html#a49faef5920860345e503023b7c84423c">  552</a></span>&#160;        <span class="keyword">inline</span> <span class="keywordtype">float</span> <a class="code" href="group__tensorNet.html#a49faef5920860345e503023b7c84423c">GetNetworkTime</a>()                                                   { <span class="keywordflow">return</span> <a class="code" href="group__tensorNet.html#ad266f93035a80dca80cd84d971e4f69b">GetProfilerTime</a>(<a class="code" href="group__tensorNet.html#ggae34d45c0faa674ef4cc0fbfc8fae5809a624bb4adf22f078ad2804595dca02992">PROFILER_NETWORK</a>, <a class="code" href="group__tensorNet.html#ggaaa4127ed22c7165a32d0474ebf97975eadbfd2a2033cd2a8df5fa51e13ff528b7">PROFILER_CUDA</a>); }</div>
<div class="line"><a name="l00553"></a><span class="lineno">  553</span>&#160;        </div>
<div class="line"><a name="l00557"></a><span class="lineno"><a class="line" href="group__tensorNet.html#ade7badd98d5790b5a58863d56e61e041">  557</a></span>&#160;        <span class="keyword">inline</span> <span class="keyword">const</span> <span class="keywordtype">char</span>* <a class="code" href="group__tensorNet.html#ade7badd98d5790b5a58863d56e61e041">GetNetworkName</a>()<span class="keyword"> const                               </span>{ <span class="keywordflow">return</span> <a class="code" href="group__tensorNet.html#a338246dc13b84166ee5ea917d84379aa">mModelFile</a>.c_str(); }</div>
<div class="line"><a name="l00558"></a><span class="lineno">  558</span>&#160;        </div>
<div class="line"><a name="l00562"></a><span class="lineno"><a class="line" href="group__tensorNet.html#ad266f93035a80dca80cd84d971e4f69b">  562</a></span>&#160;        <span class="keyword">inline</span> float2 <a class="code" href="group__tensorNet.html#ad266f93035a80dca80cd84d971e4f69b">GetProfilerTime</a>( <a class="code" href="group__tensorNet.html#gae34d45c0faa674ef4cc0fbfc8fae5809">profilerQuery</a> query )            { <a class="code" href="group__tensorNet.html#ae2e0ae17baf6e1975aaad7a7f5c60ce9">PROFILER_QUERY</a>(query); <span class="keywordflow">return</span> <a class="code" href="group__tensorNet.html#a32dbfb5b3d2cb82002ec288c237a0c9c">mProfilerTimes</a>[query]; }</div>
<div class="line"><a name="l00563"></a><span class="lineno">  563</span>&#160;        </div>
<div class="line"><a name="l00567"></a><span class="lineno"><a class="line" href="group__tensorNet.html#a27cf81b3fecf93d2e63a61220a54b393">  567</a></span>&#160;        <span class="keyword">inline</span> <span class="keywordtype">float</span> <a class="code" href="group__tensorNet.html#a27cf81b3fecf93d2e63a61220a54b393">GetProfilerTime</a>( <a class="code" href="group__tensorNet.html#gae34d45c0faa674ef4cc0fbfc8fae5809">profilerQuery</a> query, <a class="code" href="group__tensorNet.html#gaaa4127ed22c7165a32d0474ebf97975e">profilerDevice</a> device ) { <a class="code" href="group__tensorNet.html#ae2e0ae17baf6e1975aaad7a7f5c60ce9">PROFILER_QUERY</a>(query); <span class="keywordflow">return</span> (device == <a class="code" href="group__tensorNet.html#ggaaa4127ed22c7165a32d0474ebf97975eaf33631f978127920224cd10c937e78d5">PROFILER_CPU</a>) ? <a class="code" href="group__tensorNet.html#a32dbfb5b3d2cb82002ec288c237a0c9c">mProfilerTimes</a>[query].x : <a class="code" href="group__tensorNet.html#a32dbfb5b3d2cb82002ec288c237a0c9c">mProfilerTimes</a>[query].y; }</div>
<div class="line"><a name="l00568"></a><span class="lineno">  568</span>&#160;        </div>
<div class="line"><a name="l00572"></a><span class="lineno"><a class="line" href="group__tensorNet.html#afc0f50abcf6ac71e96d51eba3ed53d4b">  572</a></span>&#160;        <span class="keyword">inline</span> <span class="keywordtype">void</span> <a class="code" href="group__tensorNet.html#afc0f50abcf6ac71e96d51eba3ed53d4b">PrintProfilerTimes</a>()</div>
<div class="line"><a name="l00573"></a><span class="lineno">  573</span>&#160;        {</div>
<div class="line"><a name="l00574"></a><span class="lineno">  574</span>&#160;                <a class="code" href="group__log.html#ga228a21f91213b15d7fdce08182d825e8">LogInfo</a>(<span class="stringliteral">&quot;\n&quot;</span>);</div>
<div class="line"><a name="l00575"></a><span class="lineno">  575</span>&#160;                <a class="code" href="group__log.html#ga228a21f91213b15d7fdce08182d825e8">LogInfo</a>(<a class="code" href="group__tensorNet.html#ga3c048e603c3c16fb810eb11c36242f82">LOG_TRT</a> <span class="stringliteral">&quot;------------------------------------------------\n&quot;</span>);</div>
<div class="line"><a name="l00576"></a><span class="lineno">  576</span>&#160;                <a class="code" href="group__log.html#ga228a21f91213b15d7fdce08182d825e8">LogInfo</a>(<a class="code" href="group__tensorNet.html#ga3c048e603c3c16fb810eb11c36242f82">LOG_TRT</a> <span class="stringliteral">&quot;Timing Report %s\n&quot;</span>, <a class="code" href="group__tensorNet.html#ac74d7f0571b7782b945ff85fd6894044">GetModelPath</a>());</div>
<div class="line"><a name="l00577"></a><span class="lineno">  577</span>&#160;                <a class="code" href="group__log.html#ga228a21f91213b15d7fdce08182d825e8">LogInfo</a>(<a class="code" href="group__tensorNet.html#ga3c048e603c3c16fb810eb11c36242f82">LOG_TRT</a> <span class="stringliteral">&quot;------------------------------------------------\n&quot;</span>);</div>
<div class="line"><a name="l00578"></a><span class="lineno">  578</span>&#160; </div>
<div class="line"><a name="l00579"></a><span class="lineno">  579</span>&#160;                <span class="keywordflow">for</span>( uint32_t n=0; n &lt;= <a class="code" href="group__tensorNet.html#ggae34d45c0faa674ef4cc0fbfc8fae5809af9132edd0371e716aed4d46e3da5e9ea">PROFILER_TOTAL</a>; n++ )</div>
<div class="line"><a name="l00580"></a><span class="lineno">  580</span>&#160;                {</div>
<div class="line"><a name="l00581"></a><span class="lineno">  581</span>&#160;                        <span class="keyword">const</span> <a class="code" href="group__tensorNet.html#gae34d45c0faa674ef4cc0fbfc8fae5809">profilerQuery</a> query = (<a class="code" href="group__tensorNet.html#gae34d45c0faa674ef4cc0fbfc8fae5809">profilerQuery</a>)n;</div>
<div class="line"><a name="l00582"></a><span class="lineno">  582</span>&#160; </div>
<div class="line"><a name="l00583"></a><span class="lineno">  583</span>&#160;                        <span class="keywordflow">if</span>( <a class="code" href="group__tensorNet.html#ae2e0ae17baf6e1975aaad7a7f5c60ce9">PROFILER_QUERY</a>(query) )</div>
<div class="line"><a name="l00584"></a><span class="lineno">  584</span>&#160;                                <a class="code" href="group__log.html#ga228a21f91213b15d7fdce08182d825e8">LogInfo</a>(<a class="code" href="group__tensorNet.html#ga3c048e603c3c16fb810eb11c36242f82">LOG_TRT</a> <span class="stringliteral">&quot;%-12s  CPU %9.5fms  CUDA %9.5fms\n&quot;</span>, <a class="code" href="group__tensorNet.html#gaf219ba5ec806feca1433d20367e0f049">profilerQueryToStr</a>(query), <a class="code" href="group__tensorNet.html#a32dbfb5b3d2cb82002ec288c237a0c9c">mProfilerTimes</a>[n].x, <a class="code" href="group__tensorNet.html#a32dbfb5b3d2cb82002ec288c237a0c9c">mProfilerTimes</a>[n].y);</div>
<div class="line"><a name="l00585"></a><span class="lineno">  585</span>&#160;                }</div>
<div class="line"><a name="l00586"></a><span class="lineno">  586</span>&#160; </div>
<div class="line"><a name="l00587"></a><span class="lineno">  587</span>&#160;                <a class="code" href="group__log.html#ga228a21f91213b15d7fdce08182d825e8">LogInfo</a>(<a class="code" href="group__tensorNet.html#ga3c048e603c3c16fb810eb11c36242f82">LOG_TRT</a> <span class="stringliteral">&quot;------------------------------------------------\n\n&quot;</span>);</div>
<div class="line"><a name="l00588"></a><span class="lineno">  588</span>&#160; </div>
<div class="line"><a name="l00589"></a><span class="lineno">  589</span>&#160;                <span class="keyword">static</span> <span class="keywordtype">bool</span> first_run=<span class="keyword">true</span>;</div>
<div class="line"><a name="l00590"></a><span class="lineno">  590</span>&#160; </div>
<div class="line"><a name="l00591"></a><span class="lineno">  591</span>&#160;                <span class="keywordflow">if</span>( first_run )</div>
<div class="line"><a name="l00592"></a><span class="lineno">  592</span>&#160;                {</div>
<div class="line"><a name="l00593"></a><span class="lineno">  593</span>&#160;                        <a class="code" href="group__log.html#ga923829d777617140de2576c40e3880ed">LogWarning</a>(<a class="code" href="group__tensorNet.html#ga3c048e603c3c16fb810eb11c36242f82">LOG_TRT</a> <span class="stringliteral">&quot;note -- when processing a single image, run &#39;sudo jetson_clocks&#39; before\n&quot;</span></div>
<div class="line"><a name="l00594"></a><span class="lineno">  594</span>&#160;                                      <span class="stringliteral">&quot;                to disable DVFS for more accurate profiling/timing measurements\n\n&quot;</span>);</div>
<div class="line"><a name="l00595"></a><span class="lineno">  595</span>&#160;                        </div>
<div class="line"><a name="l00596"></a><span class="lineno">  596</span>&#160;                        first_run = <span class="keyword">false</span>;</div>
<div class="line"><a name="l00597"></a><span class="lineno">  597</span>&#160;                }</div>
<div class="line"><a name="l00598"></a><span class="lineno">  598</span>&#160;        }</div>
<div class="line"><a name="l00599"></a><span class="lineno">  599</span>&#160;        </div>
<div class="line"><a name="l00600"></a><span class="lineno">  600</span>&#160;<span class="keyword">protected</span>:</div>
<div class="line"><a name="l00601"></a><span class="lineno">  601</span>&#160; </div>
<div class="line"><a name="l00605"></a><span class="lineno">  605</span>&#160;        <a class="code" href="group__tensorNet.html#ab6e617d96e5542bef023ee9d4c96388a">tensorNet</a>();</div>
<div class="line"><a name="l00606"></a><span class="lineno">  606</span>&#160;                </div>
<div class="line"><a name="l00614"></a><span class="lineno">  614</span>&#160;        <span class="keywordtype">bool</span> <a class="code" href="group__tensorNet.html#a2e8dd909e797dfcfbb058dc6b351c586">ProcessNetwork</a>( <span class="keywordtype">bool</span> sync=<span class="keyword">true</span> );</div>
<div class="line"><a name="l00615"></a><span class="lineno">  615</span>&#160;          </div>
<div class="line"><a name="l00626"></a><span class="lineno">  626</span>&#160;        <span class="keywordtype">bool</span> <a class="code" href="group__tensorNet.html#a2fbc013f70b52f885867302446e0dca1">ProfileModel</a>( <span class="keyword">const</span> std::string&amp; deployFile, <span class="keyword">const</span> std::string&amp; modelFile,</div>
<div class="line"><a name="l00627"></a><span class="lineno">  627</span>&#160;                                    <span class="keyword">const</span> std::vector&lt;std::string&gt;&amp; inputs, <span class="keyword">const</span> std::vector&lt;Dims3&gt;&amp; inputDims,</div>
<div class="line"><a name="l00628"></a><span class="lineno">  628</span>&#160;                                    <span class="keyword">const</span> std::vector&lt;std::string&gt;&amp; outputs, uint32_t maxBatchSize, </div>
<div class="line"><a name="l00629"></a><span class="lineno">  629</span>&#160;                                    <a class="code" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a> precision, <a class="code" href="group__tensorNet.html#gaa5d3f9981cdbd91516c1474006a80fe4">deviceType</a> device, <span class="keywordtype">bool</span> allowGPUFallback,</div>
<div class="line"><a name="l00630"></a><span class="lineno">  630</span>&#160;                                    nvinfer1::IInt8Calibrator* calibrator, <span class="keywordtype">char</span>** engineStream, <span class="keywordtype">size_t</span>* engineSize );</div>
<div class="line"><a name="l00631"></a><span class="lineno">  631</span>&#160; </div>
<div class="line"><a name="l00635"></a><span class="lineno">  635</span>&#160;<span class="preprocessor">#if NV_TENSORRT_MAJOR &gt;= 8</span></div>
<div class="line"><a name="l00636"></a><span class="lineno">  636</span>&#160;        <span class="keywordtype">bool</span> <a class="code" href="group__tensorNet.html#a7a898dfb2553869cdc318ecb03e153f1">ConfigureBuilder</a>( nvinfer1::IBuilder* builder, nvinfer1::IBuilderConfig* config,  </div>
<div class="line"><a name="l00637"></a><span class="lineno">  637</span>&#160;                                           uint32_t maxBatchSize, uint32_t workspaceSize, <a class="code" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a> precision, </div>
<div class="line"><a name="l00638"></a><span class="lineno">  638</span>&#160;                                           <a class="code" href="group__tensorNet.html#gaa5d3f9981cdbd91516c1474006a80fe4">deviceType</a> device, <span class="keywordtype">bool</span> allowGPUFallback, </div>
<div class="line"><a name="l00639"></a><span class="lineno">  639</span>&#160;                                           nvinfer1::IInt8Calibrator* calibrator );</div>
<div class="line"><a name="l00640"></a><span class="lineno">  640</span>&#160;<span class="preprocessor">#else    </span></div>
<div class="line"><a name="l00641"></a><span class="lineno">  641</span>&#160;        <span class="keywordtype">bool</span> <a class="code" href="group__tensorNet.html#a7a898dfb2553869cdc318ecb03e153f1">ConfigureBuilder</a>( nvinfer1::IBuilder* builder, uint32_t maxBatchSize, </div>
<div class="line"><a name="l00642"></a><span class="lineno">  642</span>&#160;                                           uint32_t workspaceSize, <a class="code" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a> precision, </div>
<div class="line"><a name="l00643"></a><span class="lineno">  643</span>&#160;                                           <a class="code" href="group__tensorNet.html#gaa5d3f9981cdbd91516c1474006a80fe4">deviceType</a> device, <span class="keywordtype">bool</span> allowGPUFallback, </div>
<div class="line"><a name="l00644"></a><span class="lineno">  644</span>&#160;                                           nvinfer1::IInt8Calibrator* calibrator );</div>
<div class="line"><a name="l00645"></a><span class="lineno">  645</span>&#160;<span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00646"></a><span class="lineno">  646</span>&#160; </div>
<div class="line"><a name="l00650"></a><span class="lineno">  650</span>&#160;        <span class="keywordtype">bool</span> <a class="code" href="group__tensorNet.html#a6e2fe0a467929d76b20940771b8f96c3">ValidateEngine</a>( <span class="keyword">const</span> <span class="keywordtype">char</span>* model_path, <span class="keyword">const</span> <span class="keywordtype">char</span>* cache_path, <span class="keyword">const</span> <span class="keywordtype">char</span>* checksum_path );</div>
<div class="line"><a name="l00651"></a><span class="lineno">  651</span>&#160; </div>
<div class="line"><a name="l00655"></a><span class="lineno"><a class="line" href="classtensorNet_1_1Logger.html">  655</a></span>&#160;        <span class="keyword">class </span><a class="code" href="classtensorNet_1_1Logger.html">Logger</a> : <span class="keyword">public</span> nvinfer1::ILogger                 </div>
<div class="line"><a name="l00656"></a><span class="lineno">  656</span>&#160;        {</div>
<div class="line"><a name="l00657"></a><span class="lineno">  657</span>&#160;        <span class="keyword">public</span>:</div>
<div class="line"><a name="l00658"></a><span class="lineno"><a class="line" href="classtensorNet_1_1Logger.html#ac2a77ceaa57c5faaa0ea0d63f1a7a3cb">  658</a></span>&#160;                <span class="keywordtype">void</span> <a class="code" href="classtensorNet_1_1Logger.html#ac2a77ceaa57c5faaa0ea0d63f1a7a3cb">log</a>( Severity severity, <span class="keyword">const</span> <span class="keywordtype">char</span>* msg ) <a class="code" href="tensorNet_8h.html#a10a59554805ac7ce3905fd3540f98137">NOEXCEPT</a> <span class="keyword">override</span></div>
<div class="line"><a name="l00659"></a><span class="lineno">  659</span>&#160;                {</div>
<div class="line"><a name="l00660"></a><span class="lineno">  660</span>&#160;                        <span class="keywordflow">if</span>( severity == Severity::kWARNING )</div>
<div class="line"><a name="l00661"></a><span class="lineno">  661</span>&#160;                        {</div>
<div class="line"><a name="l00662"></a><span class="lineno">  662</span>&#160;                                <a class="code" href="group__log.html#ga923829d777617140de2576c40e3880ed">LogWarning</a>(<a class="code" href="group__tensorNet.html#ga3c048e603c3c16fb810eb11c36242f82">LOG_TRT</a> <span class="stringliteral">&quot;%s\n&quot;</span>, msg);</div>
<div class="line"><a name="l00663"></a><span class="lineno">  663</span>&#160;                        }</div>
<div class="line"><a name="l00664"></a><span class="lineno">  664</span>&#160;                        <span class="keywordflow">else</span> <span class="keywordflow">if</span>( severity == Severity::kINFO )</div>
<div class="line"><a name="l00665"></a><span class="lineno">  665</span>&#160;                        {</div>
<div class="line"><a name="l00666"></a><span class="lineno">  666</span>&#160;                                <a class="code" href="group__log.html#ga228a21f91213b15d7fdce08182d825e8">LogInfo</a>(<a class="code" href="group__tensorNet.html#ga3c048e603c3c16fb810eb11c36242f82">LOG_TRT</a> <span class="stringliteral">&quot;%s\n&quot;</span>, msg);</div>
<div class="line"><a name="l00667"></a><span class="lineno">  667</span>&#160;                        }</div>
<div class="line"><a name="l00668"></a><span class="lineno">  668</span>&#160;<span class="preprocessor">                #if NV_TENSORRT_MAJOR &gt;= 6</span></div>
<div class="line"><a name="l00669"></a><span class="lineno">  669</span>&#160;                        <span class="keywordflow">else</span> <span class="keywordflow">if</span>( severity == Severity::kVERBOSE )</div>
<div class="line"><a name="l00670"></a><span class="lineno">  670</span>&#160;                        {</div>
<div class="line"><a name="l00671"></a><span class="lineno">  671</span>&#160;                                <a class="code" href="group__log.html#ga98544477d87d57d0b8e2b3ac03481785">LogVerbose</a>(<a class="code" href="group__tensorNet.html#ga3c048e603c3c16fb810eb11c36242f82">LOG_TRT</a> <span class="stringliteral">&quot;%s\n&quot;</span>, msg);</div>
<div class="line"><a name="l00672"></a><span class="lineno">  672</span>&#160;                        }</div>
<div class="line"><a name="l00673"></a><span class="lineno">  673</span>&#160;<span class="preprocessor">                #endif</span></div>
<div class="line"><a name="l00674"></a><span class="lineno">  674</span>&#160;                        <span class="keywordflow">else</span></div>
<div class="line"><a name="l00675"></a><span class="lineno">  675</span>&#160;                        {</div>
<div class="line"><a name="l00676"></a><span class="lineno">  676</span>&#160;                                <a class="code" href="group__log.html#ga0f3919667d0ac0b001e44edb569d22fe">LogError</a>(<a class="code" href="group__tensorNet.html#ga3c048e603c3c16fb810eb11c36242f82">LOG_TRT</a> <span class="stringliteral">&quot;%s\n&quot;</span>, msg);</div>
<div class="line"><a name="l00677"></a><span class="lineno">  677</span>&#160;                        }</div>
<div class="line"><a name="l00678"></a><span class="lineno">  678</span>&#160;                }</div>
<div class="line"><a name="l00679"></a><span class="lineno">  679</span>&#160;        } <span class="keyword">static</span> <a class="code" href="group__tensorNet.html#a0c6f7cc68ce87e0701029d40b46d1b81">gLogger</a>;</div>
<div class="line"><a name="l00680"></a><span class="lineno">  680</span>&#160; </div>
<div class="line"><a name="l00684"></a><span class="lineno"><a class="line" href="classtensorNet_1_1Profiler.html">  684</a></span>&#160;        <span class="keyword">class </span><a class="code" href="classtensorNet_1_1Profiler.html">Profiler</a> : <span class="keyword">public</span> nvinfer1::IProfiler</div>
<div class="line"><a name="l00685"></a><span class="lineno">  685</span>&#160;        {</div>
<div class="line"><a name="l00686"></a><span class="lineno">  686</span>&#160;        <span class="keyword">public</span>:</div>
<div class="line"><a name="l00687"></a><span class="lineno"><a class="line" href="classtensorNet_1_1Profiler.html#a55a6fd3103bcd4a57379a90eff183617">  687</a></span>&#160;                <a class="code" href="classtensorNet_1_1Profiler.html#a55a6fd3103bcd4a57379a90eff183617">Profiler</a>() : <a class="code" href="classtensorNet_1_1Profiler.html#a8784d561f96bfd5a02c2bf9554f0d773">timingAccumulator</a>(0.0f)    { }</div>
<div class="line"><a name="l00688"></a><span class="lineno">  688</span>&#160;                </div>
<div class="line"><a name="l00689"></a><span class="lineno"><a class="line" href="classtensorNet_1_1Profiler.html#a10c85affab9f2e43463676e3221b93bf">  689</a></span>&#160;                <span class="keyword">virtual</span> <span class="keywordtype">void</span> <a class="code" href="classtensorNet_1_1Profiler.html#a10c85affab9f2e43463676e3221b93bf">reportLayerTime</a>(<span class="keyword">const</span> <span class="keywordtype">char</span>* layerName, <span class="keywordtype">float</span> ms) <a class="code" href="tensorNet_8h.html#a10a59554805ac7ce3905fd3540f98137">NOEXCEPT</a></div>
<div class="line"><a name="l00690"></a><span class="lineno">  690</span>&#160;                {</div>
<div class="line"><a name="l00691"></a><span class="lineno">  691</span>&#160;                        <a class="code" href="group__log.html#ga98544477d87d57d0b8e2b3ac03481785">LogVerbose</a>(<a class="code" href="group__tensorNet.html#ga3c048e603c3c16fb810eb11c36242f82">LOG_TRT</a> <span class="stringliteral">&quot;layer %s - %f ms\n&quot;</span>, layerName, ms);</div>
<div class="line"><a name="l00692"></a><span class="lineno">  692</span>&#160;                        <a class="code" href="classtensorNet_1_1Profiler.html#a8784d561f96bfd5a02c2bf9554f0d773">timingAccumulator</a> += ms;</div>
<div class="line"><a name="l00693"></a><span class="lineno">  693</span>&#160;                }</div>
<div class="line"><a name="l00694"></a><span class="lineno">  694</span>&#160;                </div>
<div class="line"><a name="l00695"></a><span class="lineno"><a class="line" href="classtensorNet_1_1Profiler.html#a8784d561f96bfd5a02c2bf9554f0d773">  695</a></span>&#160;                <span class="keywordtype">float</span> <a class="code" href="classtensorNet_1_1Profiler.html#a8784d561f96bfd5a02c2bf9554f0d773">timingAccumulator</a>;</div>
<div class="line"><a name="l00696"></a><span class="lineno">  696</span>&#160;        } <a class="code" href="group__tensorNet.html#a70f38033952477e55e2ecdc54f908968">gProfiler</a>;</div>
<div class="line"><a name="l00697"></a><span class="lineno">  697</span>&#160; </div>
<div class="line"><a name="l00701"></a><span class="lineno"><a class="line" href="group__tensorNet.html#a088c3bf591e45e52ec227491f6f299ad">  701</a></span>&#160;        <span class="keyword">inline</span> <span class="keywordtype">void</span> <a class="code" href="group__tensorNet.html#a088c3bf591e45e52ec227491f6f299ad">PROFILER_BEGIN</a>( <a class="code" href="group__tensorNet.html#gae34d45c0faa674ef4cc0fbfc8fae5809">profilerQuery</a> query )               </div>
<div class="line"><a name="l00702"></a><span class="lineno">  702</span>&#160;        { </div>
<div class="line"><a name="l00703"></a><span class="lineno">  703</span>&#160;                <span class="keyword">const</span> uint32_t evt = query*2; </div>
<div class="line"><a name="l00704"></a><span class="lineno">  704</span>&#160;                <span class="keyword">const</span> uint32_t flag = (1 &lt;&lt; query);</div>
<div class="line"><a name="l00705"></a><span class="lineno">  705</span>&#160; </div>
<div class="line"><a name="l00706"></a><span class="lineno">  706</span>&#160;                <a class="code" href="group__cudaError.html#ga5af54ef2b094a11a88feb67b327e1d19">CUDA</a>(cudaEventRecord(<a class="code" href="group__tensorNet.html#aac52fdcc0579c0426e21141636349dea">mEventsGPU</a>[evt], <a class="code" href="group__tensorNet.html#a1ed6e418a135650c7cf91498379727ae">mStream</a>)); </div>
<div class="line"><a name="l00707"></a><span class="lineno">  707</span>&#160;                <a class="code" href="group__time.html#ga741cdb5863f122d3e527c8b53e0cb3c3">timestamp</a>(&amp;<a class="code" href="group__tensorNet.html#af4cb4b37a74806164257e9529cb8ed70">mEventsCPU</a>[evt]); </div>
<div class="line"><a name="l00708"></a><span class="lineno">  708</span>&#160; </div>
<div class="line"><a name="l00709"></a><span class="lineno">  709</span>&#160;                <a class="code" href="group__tensorNet.html#a545348243b65ce04047fd10d47e1716c">mProfilerQueriesUsed</a> |= flag;</div>
<div class="line"><a name="l00710"></a><span class="lineno">  710</span>&#160;                <a class="code" href="group__tensorNet.html#a3b5be95254ce71931305f4086f23f18a">mProfilerQueriesDone</a> &amp;= ~flag;</div>
<div class="line"><a name="l00711"></a><span class="lineno">  711</span>&#160;        }</div>
<div class="line"><a name="l00712"></a><span class="lineno">  712</span>&#160; </div>
<div class="line"><a name="l00716"></a><span class="lineno"><a class="line" href="group__tensorNet.html#ac8582b9a6099e3265da4c3f9fdf804ea">  716</a></span>&#160;        <span class="keyword">inline</span> <span class="keywordtype">void</span> <a class="code" href="group__tensorNet.html#ac8582b9a6099e3265da4c3f9fdf804ea">PROFILER_END</a>( <a class="code" href="group__tensorNet.html#gae34d45c0faa674ef4cc0fbfc8fae5809">profilerQuery</a> query )         </div>
<div class="line"><a name="l00717"></a><span class="lineno">  717</span>&#160;        { </div>
<div class="line"><a name="l00718"></a><span class="lineno">  718</span>&#160;                <span class="keyword">const</span> uint32_t evt = query*2+1; </div>
<div class="line"><a name="l00719"></a><span class="lineno">  719</span>&#160; </div>
<div class="line"><a name="l00720"></a><span class="lineno">  720</span>&#160;                <a class="code" href="group__cudaError.html#ga5af54ef2b094a11a88feb67b327e1d19">CUDA</a>(cudaEventRecord(<a class="code" href="group__tensorNet.html#aac52fdcc0579c0426e21141636349dea">mEventsGPU</a>[evt])); </div>
<div class="line"><a name="l00721"></a><span class="lineno">  721</span>&#160;                <a class="code" href="group__time.html#ga741cdb5863f122d3e527c8b53e0cb3c3">timestamp</a>(&amp;<a class="code" href="group__tensorNet.html#af4cb4b37a74806164257e9529cb8ed70">mEventsCPU</a>[evt]); </div>
<div class="line"><a name="l00722"></a><span class="lineno">  722</span>&#160;                timespec cpuTime; </div>
<div class="line"><a name="l00723"></a><span class="lineno">  723</span>&#160;                <a class="code" href="group__time.html#ga3c4b729b99d06b423956e7a3a17aaeb4">timeDiff</a>(<a class="code" href="group__tensorNet.html#af4cb4b37a74806164257e9529cb8ed70">mEventsCPU</a>[evt-1], <a class="code" href="group__tensorNet.html#af4cb4b37a74806164257e9529cb8ed70">mEventsCPU</a>[evt], &amp;cpuTime);</div>
<div class="line"><a name="l00724"></a><span class="lineno">  724</span>&#160;                <a class="code" href="group__tensorNet.html#a32dbfb5b3d2cb82002ec288c237a0c9c">mProfilerTimes</a>[query].x = <a class="code" href="group__time.html#ga762b4a9f55b4fb1a50d459cc7c384b92">timeFloat</a>(cpuTime);</div>
<div class="line"><a name="l00725"></a><span class="lineno">  725</span>&#160; </div>
<div class="line"><a name="l00726"></a><span class="lineno">  726</span>&#160;                <span class="keywordflow">if</span>( <a class="code" href="group__tensorNet.html#aa8bbf97d979c62018f42cc44b5cb81e8">mEnableProfiler</a> &amp;&amp; query == <a class="code" href="group__tensorNet.html#ggae34d45c0faa674ef4cc0fbfc8fae5809a624bb4adf22f078ad2804595dca02992">PROFILER_NETWORK</a> ) </div>
<div class="line"><a name="l00727"></a><span class="lineno">  727</span>&#160;                { </div>
<div class="line"><a name="l00728"></a><span class="lineno">  728</span>&#160;                        <a class="code" href="group__log.html#ga98544477d87d57d0b8e2b3ac03481785">LogVerbose</a>(<a class="code" href="group__tensorNet.html#ga3c048e603c3c16fb810eb11c36242f82">LOG_TRT</a> <span class="stringliteral">&quot;layer network time - %f ms\n&quot;</span>, <a class="code" href="group__tensorNet.html#a70f38033952477e55e2ecdc54f908968">gProfiler</a>.<a class="code" href="classtensorNet_1_1Profiler.html#a8784d561f96bfd5a02c2bf9554f0d773">timingAccumulator</a>); </div>
<div class="line"><a name="l00729"></a><span class="lineno">  729</span>&#160;                        <a class="code" href="group__tensorNet.html#a70f38033952477e55e2ecdc54f908968">gProfiler</a>.<a class="code" href="classtensorNet_1_1Profiler.html#a8784d561f96bfd5a02c2bf9554f0d773">timingAccumulator</a> = 0.0f; </div>
<div class="line"><a name="l00730"></a><span class="lineno">  730</span>&#160;                        <a class="code" href="group__log.html#ga923829d777617140de2576c40e3880ed">LogWarning</a>(<a class="code" href="group__tensorNet.html#ga3c048e603c3c16fb810eb11c36242f82">LOG_TRT</a> <span class="stringliteral">&quot;note -- when processing a single image, run &#39;sudo jetson_clocks&#39; before\n&quot;</span></div>
<div class="line"><a name="l00731"></a><span class="lineno">  731</span>&#160;                                      <span class="stringliteral">&quot;                to disable DVFS for more accurate profiling/timing measurements\n&quot;</span>); </div>
<div class="line"><a name="l00732"></a><span class="lineno">  732</span>&#160;                }</div>
<div class="line"><a name="l00733"></a><span class="lineno">  733</span>&#160;        }</div>
<div class="line"><a name="l00734"></a><span class="lineno">  734</span>&#160;        </div>
<div class="line"><a name="l00738"></a><span class="lineno"><a class="line" href="group__tensorNet.html#ae2e0ae17baf6e1975aaad7a7f5c60ce9">  738</a></span>&#160;        <span class="keyword">inline</span> <span class="keywordtype">bool</span> <a class="code" href="group__tensorNet.html#ae2e0ae17baf6e1975aaad7a7f5c60ce9">PROFILER_QUERY</a>( <a class="code" href="group__tensorNet.html#gae34d45c0faa674ef4cc0fbfc8fae5809">profilerQuery</a> query )</div>
<div class="line"><a name="l00739"></a><span class="lineno">  739</span>&#160;        {</div>
<div class="line"><a name="l00740"></a><span class="lineno">  740</span>&#160;                <span class="keyword">const</span> uint32_t flag = (1 &lt;&lt; query);</div>
<div class="line"><a name="l00741"></a><span class="lineno">  741</span>&#160; </div>
<div class="line"><a name="l00742"></a><span class="lineno">  742</span>&#160;                <span class="keywordflow">if</span>( query == <a class="code" href="group__tensorNet.html#ggae34d45c0faa674ef4cc0fbfc8fae5809af9132edd0371e716aed4d46e3da5e9ea">PROFILER_TOTAL</a> )</div>
<div class="line"><a name="l00743"></a><span class="lineno">  743</span>&#160;                {</div>
<div class="line"><a name="l00744"></a><span class="lineno">  744</span>&#160;                        <a class="code" href="group__tensorNet.html#a32dbfb5b3d2cb82002ec288c237a0c9c">mProfilerTimes</a>[<a class="code" href="group__tensorNet.html#ggae34d45c0faa674ef4cc0fbfc8fae5809af9132edd0371e716aed4d46e3da5e9ea">PROFILER_TOTAL</a>].x = 0.0f;</div>
<div class="line"><a name="l00745"></a><span class="lineno">  745</span>&#160;                        <a class="code" href="group__tensorNet.html#a32dbfb5b3d2cb82002ec288c237a0c9c">mProfilerTimes</a>[<a class="code" href="group__tensorNet.html#ggae34d45c0faa674ef4cc0fbfc8fae5809af9132edd0371e716aed4d46e3da5e9ea">PROFILER_TOTAL</a>].y = 0.0f;</div>
<div class="line"><a name="l00746"></a><span class="lineno">  746</span>&#160; </div>
<div class="line"><a name="l00747"></a><span class="lineno">  747</span>&#160;                        <span class="keywordflow">for</span>( uint32_t n=0; n &lt; <a class="code" href="group__tensorNet.html#ggae34d45c0faa674ef4cc0fbfc8fae5809af9132edd0371e716aed4d46e3da5e9ea">PROFILER_TOTAL</a>; n++ )</div>
<div class="line"><a name="l00748"></a><span class="lineno">  748</span>&#160;                        {</div>
<div class="line"><a name="l00749"></a><span class="lineno">  749</span>&#160;                                <span class="keywordflow">if</span>( <a class="code" href="group__tensorNet.html#ae2e0ae17baf6e1975aaad7a7f5c60ce9">PROFILER_QUERY</a>((<a class="code" href="group__tensorNet.html#gae34d45c0faa674ef4cc0fbfc8fae5809">profilerQuery</a>)n) )</div>
<div class="line"><a name="l00750"></a><span class="lineno">  750</span>&#160;                                {</div>
<div class="line"><a name="l00751"></a><span class="lineno">  751</span>&#160;                                        <a class="code" href="group__tensorNet.html#a32dbfb5b3d2cb82002ec288c237a0c9c">mProfilerTimes</a>[<a class="code" href="group__tensorNet.html#ggae34d45c0faa674ef4cc0fbfc8fae5809af9132edd0371e716aed4d46e3da5e9ea">PROFILER_TOTAL</a>].x += <a class="code" href="group__tensorNet.html#a32dbfb5b3d2cb82002ec288c237a0c9c">mProfilerTimes</a>[n].x;</div>
<div class="line"><a name="l00752"></a><span class="lineno">  752</span>&#160;                                        <a class="code" href="group__tensorNet.html#a32dbfb5b3d2cb82002ec288c237a0c9c">mProfilerTimes</a>[<a class="code" href="group__tensorNet.html#ggae34d45c0faa674ef4cc0fbfc8fae5809af9132edd0371e716aed4d46e3da5e9ea">PROFILER_TOTAL</a>].y += <a class="code" href="group__tensorNet.html#a32dbfb5b3d2cb82002ec288c237a0c9c">mProfilerTimes</a>[n].y;</div>
<div class="line"><a name="l00753"></a><span class="lineno">  753</span>&#160;                                }</div>
<div class="line"><a name="l00754"></a><span class="lineno">  754</span>&#160;                        }</div>
<div class="line"><a name="l00755"></a><span class="lineno">  755</span>&#160; </div>
<div class="line"><a name="l00756"></a><span class="lineno">  756</span>&#160;                        <span class="keywordflow">return</span> <span class="keyword">true</span>;</div>
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<div class="line"><a name="l00759"></a><span class="lineno">  759</span>&#160;                {</div>
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<div class="line"><a name="l00761"></a><span class="lineno">  761</span>&#160;                        {</div>
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<div class="line"><a name="l00765"></a><span class="lineno">  765</span>&#160;                                <a class="code" href="group__tensorNet.html#a32dbfb5b3d2cb82002ec288c237a0c9c">mProfilerTimes</a>[query].y = cuda_time;</div>
<div class="line"><a name="l00766"></a><span class="lineno">  766</span>&#160;                                <a class="code" href="group__tensorNet.html#a3b5be95254ce71931305f4086f23f18a">mProfilerQueriesDone</a> |= flag;</div>
<div class="line"><a name="l00767"></a><span class="lineno">  767</span>&#160;                                <span class="comment">//mProfilerQueriesUsed &amp;= ~flag;</span></div>
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<div class="line"><a name="l00769"></a><span class="lineno">  769</span>&#160; </div>
<div class="line"><a name="l00770"></a><span class="lineno">  770</span>&#160;                        <span class="keywordflow">return</span> <span class="keyword">true</span>;</div>
<div class="line"><a name="l00771"></a><span class="lineno">  771</span>&#160;                }</div>
<div class="line"><a name="l00772"></a><span class="lineno">  772</span>&#160; </div>
<div class="line"><a name="l00773"></a><span class="lineno">  773</span>&#160;                <span class="keywordflow">return</span> <span class="keyword">false</span>;</div>
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<div class="line"><a name="l00775"></a><span class="lineno">  775</span>&#160; </div>
<div class="line"><a name="l00776"></a><span class="lineno">  776</span>&#160;<span class="keyword">protected</span>:</div>
<div class="line"><a name="l00777"></a><span class="lineno">  777</span>&#160; </div>
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<div class="line"><a name="l00781"></a><span class="lineno"><a class="line" href="group__tensorNet.html#a338246dc13b84166ee5ea917d84379aa">  781</a></span>&#160;        std::string <a class="code" href="group__tensorNet.html#a338246dc13b84166ee5ea917d84379aa">mModelFile</a>;</div>
<div class="line"><a name="l00782"></a><span class="lineno"><a class="line" href="group__tensorNet.html#a11eeaa1e454a97a5634c7fb5ea1bc23d">  782</a></span>&#160;        std::string <a class="code" href="group__tensorNet.html#a11eeaa1e454a97a5634c7fb5ea1bc23d">mMeanPath</a>;</div>
<div class="line"><a name="l00783"></a><span class="lineno"><a class="line" href="group__tensorNet.html#aaa9ac0fae88a426f1a5325886da3b009">  783</a></span>&#160;        std::string <a class="code" href="group__tensorNet.html#aaa9ac0fae88a426f1a5325886da3b009">mCacheEnginePath</a>;</div>
<div class="line"><a name="l00784"></a><span class="lineno"><a class="line" href="group__tensorNet.html#a64fccb1894b0926e54a18fa47a271c70">  784</a></span>&#160;        std::string <a class="code" href="group__tensorNet.html#a64fccb1894b0926e54a18fa47a271c70">mCacheCalibrationPath</a>;</div>
<div class="line"><a name="l00785"></a><span class="lineno"><a class="line" href="group__tensorNet.html#abc88c21d81ca66f8c10d22910c995765">  785</a></span>&#160;        std::string <a class="code" href="group__tensorNet.html#abc88c21d81ca66f8c10d22910c995765">mChecksumPath</a>;</div>
<div class="line"><a name="l00786"></a><span class="lineno">  786</span>&#160;        </div>
<div class="line"><a name="l00787"></a><span class="lineno"><a class="line" href="group__tensorNet.html#a2f14a2f4a4dfbb51b80f80a2e47a695c">  787</a></span>&#160;        <a class="code" href="group__tensorNet.html#gaa5d3f9981cdbd91516c1474006a80fe4">deviceType</a>    <a class="code" href="group__tensorNet.html#a2f14a2f4a4dfbb51b80f80a2e47a695c">mDevice</a>;</div>
<div class="line"><a name="l00788"></a><span class="lineno"><a class="line" href="group__tensorNet.html#a164c1dcf9dcbc085c1b421855eda665f">  788</a></span>&#160;        <a class="code" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a> <a class="code" href="group__tensorNet.html#a164c1dcf9dcbc085c1b421855eda665f">mPrecision</a>;</div>
<div class="line"><a name="l00789"></a><span class="lineno"><a class="line" href="group__tensorNet.html#ab5c88cf4590b53804ebedaa292d1402c">  789</a></span>&#160;        <a class="code" href="group__tensorNet.html#ga5d4597e0e7beae7133d542e220528725">modelType</a>     <a class="code" href="group__tensorNet.html#ab5c88cf4590b53804ebedaa292d1402c">mModelType</a>;</div>
<div class="line"><a name="l00790"></a><span class="lineno"><a class="line" href="group__tensorNet.html#a1ed6e418a135650c7cf91498379727ae">  790</a></span>&#160;        cudaStream_t  <a class="code" href="group__tensorNet.html#a1ed6e418a135650c7cf91498379727ae">mStream</a>;</div>
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<div class="line"><a name="l00792"></a><span class="lineno"><a class="line" href="group__tensorNet.html#af4cb4b37a74806164257e9529cb8ed70">  792</a></span>&#160;        timespec      <a class="code" href="group__tensorNet.html#af4cb4b37a74806164257e9529cb8ed70">mEventsCPU</a>[<a class="code" href="group__tensorNet.html#ggae34d45c0faa674ef4cc0fbfc8fae5809af9132edd0371e716aed4d46e3da5e9ea">PROFILER_TOTAL</a> * 2];</div>
<div class="line"><a name="l00793"></a><span class="lineno">  793</span>&#160; </div>
<div class="line"><a name="l00794"></a><span class="lineno"><a class="line" href="group__tensorNet.html#a275ce2318a63dcaafc1e0120a53fe606">  794</a></span>&#160;        nvinfer1::IRuntime* <a class="code" href="group__tensorNet.html#a275ce2318a63dcaafc1e0120a53fe606">mInfer</a>;</div>
<div class="line"><a name="l00795"></a><span class="lineno"><a class="line" href="group__tensorNet.html#ad6d2272a2560bec119fa570438e3eb19">  795</a></span>&#160;        nvinfer1::ICudaEngine* <a class="code" href="group__tensorNet.html#ad6d2272a2560bec119fa570438e3eb19">mEngine</a>;</div>
<div class="line"><a name="l00796"></a><span class="lineno"><a class="line" href="group__tensorNet.html#a2c745474e60145ee826b53e294e7f478">  796</a></span>&#160;        nvinfer1::IExecutionContext* <a class="code" href="group__tensorNet.html#a2c745474e60145ee826b53e294e7f478">mContext</a>;</div>
<div class="line"><a name="l00797"></a><span class="lineno">  797</span>&#160;        </div>
<div class="line"><a name="l00798"></a><span class="lineno"><a class="line" href="group__tensorNet.html#a32dbfb5b3d2cb82002ec288c237a0c9c">  798</a></span>&#160;        float2   <a class="code" href="group__tensorNet.html#a32dbfb5b3d2cb82002ec288c237a0c9c">mProfilerTimes</a>[<a class="code" href="group__tensorNet.html#ggae34d45c0faa674ef4cc0fbfc8fae5809af9132edd0371e716aed4d46e3da5e9ea">PROFILER_TOTAL</a> + 1];</div>
<div class="line"><a name="l00799"></a><span class="lineno"><a class="line" href="group__tensorNet.html#a545348243b65ce04047fd10d47e1716c">  799</a></span>&#160;        uint32_t <a class="code" href="group__tensorNet.html#a545348243b65ce04047fd10d47e1716c">mProfilerQueriesUsed</a>;</div>
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<div class="line"><a name="l00803"></a><span class="lineno"><a class="line" href="group__tensorNet.html#aa8bbf97d979c62018f42cc44b5cb81e8">  803</a></span>&#160;        <span class="keywordtype">bool</span>        <a class="code" href="group__tensorNet.html#aa8bbf97d979c62018f42cc44b5cb81e8">mEnableProfiler</a>;</div>
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<div class="line"><a name="l00805"></a><span class="lineno"><a class="line" href="group__tensorNet.html#a8e7b5913f3f54d4bb0e6aa8e6071a74a">  805</a></span>&#160;        <span class="keywordtype">bool</span>        <a class="code" href="group__tensorNet.html#a8e7b5913f3f54d4bb0e6aa8e6071a74a">mAllowGPUFallback</a>;</div>
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<div class="line"><a name="l00807"></a><span class="lineno">  807</span>&#160; </div>
<div class="line"><a name="l00808"></a><span class="lineno"><a class="line" href="structtensorNet_1_1layerInfo.html">  808</a></span>&#160;        <span class="keyword">struct </span><a class="code" href="structtensorNet_1_1layerInfo.html">layerInfo</a></div>
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<div class="line"><a name="l00817"></a><span class="lineno">  817</span>&#160;        </div>
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<div class="line"><a name="l00819"></a><span class="lineno"><a class="line" href="group__tensorNet.html#afcdbdb26dc6e5117f867c83e635a0250">  819</a></span>&#160;        std::vector&lt;layerInfo&gt; <a class="code" href="group__tensorNet.html#afcdbdb26dc6e5117f867c83e635a0250">mOutputs</a>;</div>
<div class="line"><a name="l00820"></a><span class="lineno">  820</span>&#160;};</div>
<div class="line"><a name="l00821"></a><span class="lineno">  821</span>&#160; </div>
<div class="line"><a name="l00822"></a><span class="lineno">  822</span>&#160;<span class="preprocessor">#endif</span></div>
</div><!-- fragment --></div><!-- contents -->
</div><!-- doc-content -->
<div class="ttc" id="agroup__tensorNet_html_ae88436e652afdd7bceef7cb7c5fde7a6"><div class="ttname"><a href="group__tensorNet.html#ae88436e652afdd7bceef7cb7c5fde7a6">tensorNet::DetectNativePrecisions</a></div><div class="ttdeci">static std::vector&lt; precisionType &gt; DetectNativePrecisions(deviceType device=DEVICE_GPU)</div><div class="ttdoc">Detect the precisions supported natively on a device.</div></div>
<div class="ttc" id="agroup__tensorNet_html_ggaa5d3f9981cdbd91516c1474006a80fe4a4950aeb02ff7fba02eb2fd2437788399"><div class="ttname"><a href="group__tensorNet.html#ggaa5d3f9981cdbd91516c1474006a80fe4a4950aeb02ff7fba02eb2fd2437788399">DEVICE_DLA_0</a></div><div class="ttdeci">@ DEVICE_DLA_0</div><div class="ttdoc">Deep Learning Accelerator (DLA) Core 0 (only on Jetson Xavier)</div><div class="ttdef"><b>Definition:</b> tensorNet.h:133</div></div>
<div class="ttc" id="aclasstensorNet_1_1Logger_html"><div class="ttname"><a href="classtensorNet_1_1Logger.html">tensorNet::Logger</a></div><div class="ttdoc">Logger class for GIE info/warning/errors.</div><div class="ttdef"><b>Definition:</b> tensorNet.h:655</div></div>
<div class="ttc" id="agroup__tensorNet_html_afb38b5f171025e987a00214cc4379ca9"><div class="ttname"><a href="group__tensorNet.html#afb38b5f171025e987a00214cc4379ca9">tensorNet::GetPrecision</a></div><div class="ttdeci">precisionType GetPrecision() const</div><div class="ttdoc">Retrieve the type of precision being used.</div><div class="ttdef"><b>Definition:</b> tensorNet.h:412</div></div>
<div class="ttc" id="agroup__tensorNet_html_gga5d4597e0e7beae7133d542e220528725ad8c909322673d53ee28de66aa57bcccd"><div class="ttname"><a href="group__tensorNet.html#gga5d4597e0e7beae7133d542e220528725ad8c909322673d53ee28de66aa57bcccd">MODEL_UFF</a></div><div class="ttdeci">@ MODEL_UFF</div><div class="ttdoc">UFF.</div><div class="ttdef"><b>Definition:</b> tensorNet.h:160</div></div>
<div class="ttc" id="agroup__tensorNet_html_aa3bf1a3bf1fca38b39a200b4d8f727b2"><div class="ttname"><a href="group__tensorNet.html#aa3bf1a3bf1fca38b39a200b4d8f727b2">tensorNet::DetectNativePrecision</a></div><div class="ttdeci">static bool DetectNativePrecision(const std::vector&lt; precisionType &gt; &amp;nativeTypes, precisionType type)</div><div class="ttdoc">Detect if a particular precision is supported natively.</div></div>
<div class="ttc" id="agroup__cudaError_html_ga5af54ef2b094a11a88feb67b327e1d19"><div class="ttname"><a href="group__cudaError.html#ga5af54ef2b094a11a88feb67b327e1d19">CUDA</a></div><div class="ttdeci">#define CUDA(x)</div><div class="ttdoc">Execute a CUDA call and print out any errors.</div><div class="ttdef"><b>Definition:</b> cudaUtility.h:41</div></div>
<div class="ttc" id="agroup__tensorNet_html_a2e8dd909e797dfcfbb058dc6b351c586"><div class="ttname"><a href="group__tensorNet.html#a2e8dd909e797dfcfbb058dc6b351c586">tensorNet::ProcessNetwork</a></div><div class="ttdeci">bool ProcessNetwork(bool sync=true)</div><div class="ttdoc">Execute processing of the network.</div></div>
<div class="ttc" id="agroup__tensorNet_html_gga5d4597e0e7beae7133d542e220528725aad94b3fe48299211488aae3c133721b1"><div class="ttname"><a href="group__tensorNet.html#gga5d4597e0e7beae7133d542e220528725aad94b3fe48299211488aae3c133721b1">MODEL_CUSTOM</a></div><div class="ttdeci">@ MODEL_CUSTOM</div><div class="ttdoc">Created directly with TensorRT API.</div><div class="ttdef"><b>Definition:</b> tensorNet.h:157</div></div>
<div class="ttc" id="astructtensorNet_1_1layerInfo_html_af3b06eaa5c33ace64e1f5a49630cac2f"><div class="ttname"><a href="structtensorNet_1_1layerInfo.html#af3b06eaa5c33ace64e1f5a49630cac2f">tensorNet::layerInfo::binding</a></div><div class="ttdeci">uint32_t binding</div><div class="ttdef"><b>Definition:</b> tensorNet.h:813</div></div>
<div class="ttc" id="agroup__log_html_ga228a21f91213b15d7fdce08182d825e8"><div class="ttname"><a href="group__log.html#ga228a21f91213b15d7fdce08182d825e8">LogInfo</a></div><div class="ttdeci">#define LogInfo(format, args...)</div><div class="ttdoc">Log a printf-style info message (Log::INFO)</div><div class="ttdef"><b>Definition:</b> logging.h:168</div></div>
<div class="ttc" id="agroup__tensorNet_html_a8e7b5913f3f54d4bb0e6aa8e6071a74a"><div class="ttname"><a href="group__tensorNet.html#a8e7b5913f3f54d4bb0e6aa8e6071a74a">tensorNet::mAllowGPUFallback</a></div><div class="ttdeci">bool mAllowGPUFallback</div><div class="ttdef"><b>Definition:</b> tensorNet.h:805</div></div>
<div class="ttc" id="agroup__time_html_ga762b4a9f55b4fb1a50d459cc7c384b92"><div class="ttname"><a href="group__time.html#ga762b4a9f55b4fb1a50d459cc7c384b92">timeFloat</a></div><div class="ttdeci">float timeFloat(const timespec &amp;a)</div><div class="ttdoc">Convert to 32-bit float (in milliseconds).</div><div class="ttdef"><b>Definition:</b> timespec.h:149</div></div>
<div class="ttc" id="agroup__tensorNet_html_ga85f7b445f4341d24c65bb3bbc4a3204c"><div class="ttname"><a href="group__tensorNet.html#ga85f7b445f4341d24c65bb3bbc4a3204c">modelTypeFromStr</a></div><div class="ttdeci">modelType modelTypeFromStr(const char *str)</div><div class="ttdoc">Parse the model format from a string.</div></div>
<div class="ttc" id="agroup__tensorNet_html_a9dd2db089176ae6878e9ea7dd8fd80c3"><div class="ttname"><a href="group__tensorNet.html#a9dd2db089176ae6878e9ea7dd8fd80c3">tensorNet::GetNetworkFPS</a></div><div class="ttdeci">float GetNetworkFPS()</div><div class="ttdoc">Retrieve the network frames per second (FPS).</div><div class="ttdef"><b>Definition:</b> tensorNet.h:547</div></div>
<div class="ttc" id="astructtensorNet_1_1layerInfo_html_a1b51ab468f77ef7fd5524063e972ea11"><div class="ttname"><a href="structtensorNet_1_1layerInfo.html#a1b51ab468f77ef7fd5524063e972ea11">tensorNet::layerInfo::size</a></div><div class="ttdeci">uint32_t size</div><div class="ttdef"><b>Definition:</b> tensorNet.h:812</div></div>
<div class="ttc" id="agroup__tensorNet_html_a338246dc13b84166ee5ea917d84379aa"><div class="ttname"><a href="group__tensorNet.html#a338246dc13b84166ee5ea917d84379aa">tensorNet::mModelFile</a></div><div class="ttdeci">std::string mModelFile</div><div class="ttdef"><b>Definition:</b> tensorNet.h:781</div></div>
<div class="ttc" id="agroup__time_html_ga741cdb5863f122d3e527c8b53e0cb3c3"><div class="ttname"><a href="group__time.html#ga741cdb5863f122d3e527c8b53e0cb3c3">timestamp</a></div><div class="ttdeci">void timestamp(timespec *timestampOut)</div><div class="ttdoc">Retrieve a timestamp of the current system time.</div><div class="ttdef"><b>Definition:</b> timespec.h:37</div></div>
<div class="ttc" id="agroup__tensorNet_html_ggaaa4127ed22c7165a32d0474ebf97975eaf33631f978127920224cd10c937e78d5"><div class="ttname"><a href="group__tensorNet.html#ggaaa4127ed22c7165a32d0474ebf97975eaf33631f978127920224cd10c937e78d5">PROFILER_CPU</a></div><div class="ttdeci">@ PROFILER_CPU</div><div class="ttdoc">CPU walltime.</div><div class="ttdef"><b>Definition:</b> tensorNet.h:208</div></div>
<div class="ttc" id="agroup__tensorNet_html_a2e63d4670461814bd863ee0d9bd41526"><div class="ttname"><a href="group__tensorNet.html#a2e63d4670461814bd863ee0d9bd41526">tensorNet::LoadNetwork</a></div><div class="ttdeci">bool LoadNetwork(const char *prototxt, const char *model, const char *mean=NULL, const char *input_blob=&quot;data&quot;, const char *output_blob=&quot;prob&quot;, uint32_t maxBatchSize=DEFAULT_MAX_BATCH_SIZE, precisionType precision=TYPE_FASTEST, deviceType device=DEVICE_GPU, bool allowGPUFallback=true, nvinfer1::IInt8Calibrator *calibrator=NULL, cudaStream_t stream=NULL)</div><div class="ttdoc">Load a new network instance.</div></div>
<div class="ttc" id="agroup__tensorNet_html_ggaac6604fd52c6e5db82877390e0378623a085813e6021d0d8884d768725151a526"><div class="ttname"><a href="group__tensorNet.html#ggaac6604fd52c6e5db82877390e0378623a085813e6021d0d8884d768725151a526">TYPE_FP16</a></div><div class="ttdeci">@ TYPE_FP16</div><div class="ttdoc">16-bit floating-point half precision (FP16)</div><div class="ttdef"><b>Definition:</b> tensorNet.h:107</div></div>
<div class="ttc" id="agroup__tensorNet_html_ga85c110403b6c661b4a7042fc319f39b0"><div class="ttname"><a href="group__tensorNet.html#ga85c110403b6c661b4a7042fc319f39b0">deviceTypeToStr</a></div><div class="ttdeci">const char * deviceTypeToStr(deviceType type)</div><div class="ttdoc">Stringize function that returns deviceType in text.</div></div>
<div class="ttc" id="agroup__tensorNet_html_a624881afe27acd2b2fff0f0f75308ea2"><div class="ttname"><a href="group__tensorNet.html#a624881afe27acd2b2fff0f0f75308ea2">tensorNet::GetPrototxtPath</a></div><div class="ttdeci">const char * GetPrototxtPath() const</div><div class="ttdoc">Retrieve the path to the network prototxt file.</div><div class="ttdef"><b>Definition:</b> tensorNet.h:462</div></div>
<div class="ttc" id="agroup__tensorNet_html_aa8bbf97d979c62018f42cc44b5cb81e8"><div class="ttname"><a href="group__tensorNet.html#aa8bbf97d979c62018f42cc44b5cb81e8">tensorNet::mEnableProfiler</a></div><div class="ttdeci">bool mEnableProfiler</div><div class="ttdef"><b>Definition:</b> tensorNet.h:803</div></div>
<div class="ttc" id="agroup__tensorNet_html_gga5d4597e0e7beae7133d542e220528725ad0f2ee11de0bfff76dace6976463556b"><div class="ttname"><a href="group__tensorNet.html#gga5d4597e0e7beae7133d542e220528725ad0f2ee11de0bfff76dace6976463556b">MODEL_ENGINE</a></div><div class="ttdeci">@ MODEL_ENGINE</div><div class="ttdoc">TensorRT engine/plan.</div><div class="ttdef"><b>Definition:</b> tensorNet.h:161</div></div>
<div class="ttc" id="agroup__tensorNet_html_ae1486438dcdbe0d7f5e88e5336a42efa"><div class="ttname"><a href="group__tensorNet.html#ae1486438dcdbe0d7f5e88e5336a42efa">tensorNet::GetOutputSize</a></div><div class="ttdeci">uint32_t GetOutputSize(uint32_t layer=0) const</div><div class="ttdoc">Retrieve the size (in bytes) of network output layer.</div><div class="ttdef"><b>Definition:</b> tensorNet.h:537</div></div>
<div class="ttc" id="agroup__tensorNet_html_a0a09d691ea080bd9734c5782c8fff6fd"><div class="ttname"><a href="group__tensorNet.html#a0a09d691ea080bd9734c5782c8fff6fd">tensorNet::IsModelType</a></div><div class="ttdeci">bool IsModelType(modelType type) const</div><div class="ttdoc">Return true if the model is of the specified format.</div><div class="ttdef"><b>Definition:</b> tensorNet.h:482</div></div>
<div class="ttc" id="acudaUtility_8h_html"><div class="ttname"><a href="cudaUtility_8h.html">cudaUtility.h</a></div></div>
<div class="ttc" id="agroup__tensorNet_html_a6e2fe0a467929d76b20940771b8f96c3"><div class="ttname"><a href="group__tensorNet.html#a6e2fe0a467929d76b20940771b8f96c3">tensorNet::ValidateEngine</a></div><div class="ttdeci">bool ValidateEngine(const char *model_path, const char *cache_path, const char *checksum_path)</div><div class="ttdoc">Validate that the model already has a built TensorRT engine that exists and doesn't need updating.</div></div>
<div class="ttc" id="agroup__tensorNet_html_ggaa5d3f9981cdbd91516c1474006a80fe4aeaef16f066c95dd987fbde765b8b30b2"><div class="ttname"><a href="group__tensorNet.html#ggaa5d3f9981cdbd91516c1474006a80fe4aeaef16f066c95dd987fbde765b8b30b2">DEVICE_DLA</a></div><div class="ttdeci">@ DEVICE_DLA</div><div class="ttdoc">Deep Learning Accelerator (DLA) Core 0 (only on Jetson Xavier)</div><div class="ttdef"><b>Definition:</b> tensorNet.h:132</div></div>
<div class="ttc" id="agroup__tensorNet_html_a3413eb0ad4f240f457f192f39e2e03e8"><div class="ttname"><a href="group__tensorNet.html#a3413eb0ad4f240f457f192f39e2e03e8">tensorNet::EnableLayerProfiler</a></div><div class="ttdeci">void EnableLayerProfiler()</div><div class="ttdoc">Manually enable layer profiling times.</div></div>
<div class="ttc" id="agroup__tensorNet_html_gaaa4127ed22c7165a32d0474ebf97975e"><div class="ttname"><a href="group__tensorNet.html#gaaa4127ed22c7165a32d0474ebf97975e">profilerDevice</a></div><div class="ttdeci">profilerDevice</div><div class="ttdoc">Profiler device.</div><div class="ttdef"><b>Definition:</b> tensorNet.h:206</div></div>
<div class="ttc" id="agroup__tensorNet_html_ggaac6604fd52c6e5db82877390e0378623a12cf69049b0ce2b80538213ab4ee4908"><div class="ttname"><a href="group__tensorNet.html#ggaac6604fd52c6e5db82877390e0378623a12cf69049b0ce2b80538213ab4ee4908">TYPE_INT8</a></div><div class="ttdeci">@ TYPE_INT8</div><div class="ttdoc">8-bit integer precision (INT8)</div><div class="ttdef"><b>Definition:</b> tensorNet.h:108</div></div>
<div class="ttc" id="agroup__tensorNet_html_ab6e617d96e5542bef023ee9d4c96388a"><div class="ttname"><a href="group__tensorNet.html#ab6e617d96e5542bef023ee9d4c96388a">tensorNet::tensorNet</a></div><div class="ttdeci">tensorNet()</div><div class="ttdoc">Constructor.</div></div>
<div class="ttc" id="aclasstensorNet_1_1Profiler_html_a10c85affab9f2e43463676e3221b93bf"><div class="ttname"><a href="classtensorNet_1_1Profiler.html#a10c85affab9f2e43463676e3221b93bf">tensorNet::Profiler::reportLayerTime</a></div><div class="ttdeci">virtual void reportLayerTime(const char *layerName, float ms) NOEXCEPT</div><div class="ttdef"><b>Definition:</b> tensorNet.h:689</div></div>
<div class="ttc" id="agroup__tensorNet_html_ga1d1f73be994173912e9d964af1122ee1"><div class="ttname"><a href="group__tensorNet.html#ga1d1f73be994173912e9d964af1122ee1">precisionTypeToStr</a></div><div class="ttdeci">const char * precisionTypeToStr(precisionType type)</div><div class="ttdoc">Stringize function that returns precisionType in text.</div></div>
<div class="ttc" id="agroup__tensorNet_html_a6b8e8dba05bc5c677027913d8c64f259"><div class="ttname"><a href="group__tensorNet.html#a6b8e8dba05bc5c677027913d8c64f259">tensorNet::IsPrecision</a></div><div class="ttdeci">bool IsPrecision(precisionType type) const</div><div class="ttdoc">Check if a particular precision is being used.</div><div class="ttdef"><b>Definition:</b> tensorNet.h:417</div></div>
<div class="ttc" id="agroup__tensorNet_html_abadb712a0b45e8dc28481db3e79d1d7e"><div class="ttname"><a href="group__tensorNet.html#abadb712a0b45e8dc28481db3e79d1d7e">tensorNet::mWorkspaceSize</a></div><div class="ttdeci">uint32_t mWorkspaceSize</div><div class="ttdef"><b>Definition:</b> tensorNet.h:801</div></div>
<div class="ttc" id="agroup__tensorNet_html_a11eeaa1e454a97a5634c7fb5ea1bc23d"><div class="ttname"><a href="group__tensorNet.html#a11eeaa1e454a97a5634c7fb5ea1bc23d">tensorNet::mMeanPath</a></div><div class="ttdeci">std::string mMeanPath</div><div class="ttdef"><b>Definition:</b> tensorNet.h:782</div></div>
<div class="ttc" id="agroup__tensorNet_html_ga3c048e603c3c16fb810eb11c36242f82"><div class="ttname"><a href="group__tensorNet.html#ga3c048e603c3c16fb810eb11c36242f82">LOG_TRT</a></div><div class="ttdeci">#define LOG_TRT</div><div class="ttdoc">Prefix used for tagging printed log output from TensorRT.</div><div class="ttdef"><b>Definition:</b> tensorNet.h:94</div></div>
<div class="ttc" id="agroup__tensorNet_html_ggae34d45c0faa674ef4cc0fbfc8fae5809a8cef88bc690e0a794987ade986169ee5"><div class="ttname"><a href="group__tensorNet.html#ggae34d45c0faa674ef4cc0fbfc8fae5809a8cef88bc690e0a794987ade986169ee5">PROFILER_VISUALIZE</a></div><div class="ttdeci">@ PROFILER_VISUALIZE</div><div class="ttdef"><b>Definition:</b> tensorNet.h:192</div></div>
<div class="ttc" id="agroup__tensorNet_html_a70f38033952477e55e2ecdc54f908968"><div class="ttname"><a href="group__tensorNet.html#a70f38033952477e55e2ecdc54f908968">tensorNet::gProfiler</a></div><div class="ttdeci">tensorNet::Profiler gProfiler</div></div>
<div class="ttc" id="aclasstensorNet_1_1Logger_html_ac2a77ceaa57c5faaa0ea0d63f1a7a3cb"><div class="ttname"><a href="classtensorNet_1_1Logger.html#ac2a77ceaa57c5faaa0ea0d63f1a7a3cb">tensorNet::Logger::log</a></div><div class="ttdeci">void log(Severity severity, const char *msg) NOEXCEPT override</div><div class="ttdef"><b>Definition:</b> tensorNet.h:658</div></div>
<div class="ttc" id="agroup__tensorNet_html_a32dbfb5b3d2cb82002ec288c237a0c9c"><div class="ttname"><a href="group__tensorNet.html#a32dbfb5b3d2cb82002ec288c237a0c9c">tensorNet::mProfilerTimes</a></div><div class="ttdeci">float2 mProfilerTimes[PROFILER_TOTAL+1]</div><div class="ttdef"><b>Definition:</b> tensorNet.h:798</div></div>
<div class="ttc" id="agroup__tensorNet_html_gaf219ba5ec806feca1433d20367e0f049"><div class="ttname"><a href="group__tensorNet.html#gaf219ba5ec806feca1433d20367e0f049">profilerQueryToStr</a></div><div class="ttdeci">const char * profilerQueryToStr(profilerQuery query)</div><div class="ttdoc">Stringize function that returns profilerQuery in text.</div></div>
<div class="ttc" id="astructtensorNet_1_1layerInfo_html_a4c6c4cc012510a1f08600a81f91dc30e"><div class="ttname"><a href="structtensorNet_1_1layerInfo.html#a4c6c4cc012510a1f08600a81f91dc30e">tensorNet::layerInfo::CPU</a></div><div class="ttdeci">float * CPU</div><div class="ttdef"><b>Definition:</b> tensorNet.h:814</div></div>
<div class="ttc" id="agroup__tensorNet_html_gae34d45c0faa674ef4cc0fbfc8fae5809"><div class="ttname"><a href="group__tensorNet.html#gae34d45c0faa674ef4cc0fbfc8fae5809">profilerQuery</a></div><div class="ttdeci">profilerQuery</div><div class="ttdoc">Profiling queries.</div><div class="ttdef"><b>Definition:</b> tensorNet.h:187</div></div>
<div class="ttc" id="agroup__tensorNet_html_acb8076f6ab8d13b6507140826cf438d8"><div class="ttname"><a href="group__tensorNet.html#acb8076f6ab8d13b6507140826cf438d8">tensorNet::LoadEngine</a></div><div class="ttdeci">bool LoadEngine(const char *engine_filename, const std::vector&lt; std::string &gt; &amp;input_blobs, const std::vector&lt; std::string &gt; &amp;output_blobs, nvinfer1::IPluginFactory *pluginFactory=NULL, deviceType device=DEVICE_GPU, cudaStream_t stream=NULL)</div><div class="ttdoc">Load a network instance from a serialized engine plan file.</div></div>
<div class="ttc" id="agroup__tensorNet_html_ade7badd98d5790b5a58863d56e61e041"><div class="ttname"><a href="group__tensorNet.html#ade7badd98d5790b5a58863d56e61e041">tensorNet::GetNetworkName</a></div><div class="ttdeci">const char * GetNetworkName() const</div><div class="ttdoc">Retrieve the network name (it's filename).</div><div class="ttdef"><b>Definition:</b> tensorNet.h:557</div></div>
<div class="ttc" id="acommandLine_8h_html"><div class="ttname"><a href="commandLine_8h.html">commandLine.h</a></div></div>
<div class="ttc" id="agroup__tensorNet_html_ggaa5d3f9981cdbd91516c1474006a80fe4adc7f3f88455afa81458863e5b3092e4b"><div class="ttname"><a href="group__tensorNet.html#ggaa5d3f9981cdbd91516c1474006a80fe4adc7f3f88455afa81458863e5b3092e4b">DEVICE_GPU</a></div><div class="ttdeci">@ DEVICE_GPU</div><div class="ttdoc">GPU (if multiple GPUs are present, a specific GPU can be selected with cudaSetDevice()</div><div class="ttdef"><b>Definition:</b> tensorNet.h:131</div></div>
<div class="ttc" id="agroup__tensorNet_html_ga5d4597e0e7beae7133d542e220528725"><div class="ttname"><a href="group__tensorNet.html#ga5d4597e0e7beae7133d542e220528725">modelType</a></div><div class="ttdeci">modelType</div><div class="ttdoc">Enumeration indicating the format of the model that's imported in TensorRT (either caffe,...</div><div class="ttdef"><b>Definition:</b> tensorNet.h:155</div></div>
<div class="ttc" id="agroup__tensorNet_html_ggaaa4127ed22c7165a32d0474ebf97975eadbfd2a2033cd2a8df5fa51e13ff528b7"><div class="ttname"><a href="group__tensorNet.html#ggaaa4127ed22c7165a32d0474ebf97975eadbfd2a2033cd2a8df5fa51e13ff528b7">PROFILER_CUDA</a></div><div class="ttdeci">@ PROFILER_CUDA</div><div class="ttdoc">CUDA kernel time.</div><div class="ttdef"><b>Definition:</b> tensorNet.h:209</div></div>
<div class="ttc" id="aclasstensorNet_1_1Profiler_html_a8784d561f96bfd5a02c2bf9554f0d773"><div class="ttname"><a href="classtensorNet_1_1Profiler.html#a8784d561f96bfd5a02c2bf9554f0d773">tensorNet::Profiler::timingAccumulator</a></div><div class="ttdeci">float timingAccumulator</div><div class="ttdef"><b>Definition:</b> tensorNet.h:695</div></div>
<div class="ttc" id="atensorNet_8h_html_a64c8f3dfeacfa962ff9e23c586aedd1b"><div class="ttname"><a href="tensorNet_8h.html#a64c8f3dfeacfa962ff9e23c586aedd1b">Dims3</a></div><div class="ttdeci">nvinfer1::Dims3 Dims3</div><div class="ttdef"><b>Definition:</b> tensorNet.h:58</div></div>
<div class="ttc" id="agroup__tensorNet_html_abe33fae5332296e2d917cb4ce435e255"><div class="ttname"><a href="group__tensorNet.html#abe33fae5332296e2d917cb4ce435e255">tensorNet::FindFastestPrecision</a></div><div class="ttdeci">static precisionType FindFastestPrecision(deviceType device=DEVICE_GPU, bool allowInt8=true)</div><div class="ttdoc">Determine the fastest native precision on a device.</div></div>
<div class="ttc" id="agroup__tensorNet_html_afc0f50abcf6ac71e96d51eba3ed53d4b"><div class="ttname"><a href="group__tensorNet.html#afc0f50abcf6ac71e96d51eba3ed53d4b">tensorNet::PrintProfilerTimes</a></div><div class="ttdeci">void PrintProfilerTimes()</div><div class="ttdoc">Print the profiler times (in millseconds).</div><div class="ttdef"><b>Definition:</b> tensorNet.h:572</div></div>
<div class="ttc" id="acudaPointCloud_8h_html_ad9bd89745d72dbc52651f62814eed36d"><div class="ttname"><a href="cudaPointCloud_8h.html#ad9bd89745d72dbc52651f62814eed36d">classID</a></div><div class="ttdeci">uint8_t classID</div><div class="ttdoc">The class ID of the point.</div><div class="ttdef"><b>Definition:</b> cudaPointCloud.h:17</div></div>
<div class="ttc" id="agroup__tensorNet_html_a2d75ef6f579d1a71ff472bfafd0b7795"><div class="ttname"><a href="group__tensorNet.html#a2d75ef6f579d1a71ff472bfafd0b7795">tensorNet::GetInputWidth</a></div><div class="ttdeci">uint32_t GetInputWidth(uint32_t layer=0) const</div><div class="ttdoc">Retrieve the width of network input layer.</div><div class="ttdef"><b>Definition:</b> tensorNet.h:502</div></div>
<div class="ttc" id="agroup__tensorNet_html_a613679e8ee5315f3b5b16a39011ba76e"><div class="ttname"><a href="group__tensorNet.html#a613679e8ee5315f3b5b16a39011ba76e">tensorNet::GetOutputHeight</a></div><div class="ttdeci">uint32_t GetOutputHeight(uint32_t layer=0) const</div><div class="ttdoc">Retrieve the height of network output layer.</div><div class="ttdef"><b>Definition:</b> tensorNet.h:532</div></div>
<div class="ttc" id="agroup__tensorNet_html_gaa5d3f9981cdbd91516c1474006a80fe4"><div class="ttname"><a href="group__tensorNet.html#gaa5d3f9981cdbd91516c1474006a80fe4">deviceType</a></div><div class="ttdeci">deviceType</div><div class="ttdoc">Enumeration for indicating the desired device that the network should run on, if available in hardwar...</div><div class="ttdef"><b>Definition:</b> tensorNet.h:129</div></div>
<div class="ttc" id="agroup__tensorNet_html_a1ed6e418a135650c7cf91498379727ae"><div class="ttname"><a href="group__tensorNet.html#a1ed6e418a135650c7cf91498379727ae">tensorNet::mStream</a></div><div class="ttdeci">cudaStream_t mStream</div><div class="ttdef"><b>Definition:</b> tensorNet.h:790</div></div>
<div class="ttc" id="agroup__tensorNet_html_acfa7f1f01b46f658ffc96f8a002e8d48"><div class="ttname"><a href="group__tensorNet.html#acfa7f1f01b46f658ffc96f8a002e8d48">tensorNet::GetModelType</a></div><div class="ttdeci">modelType GetModelType() const</div><div class="ttdoc">Retrieve the format of the network model.</div><div class="ttdef"><b>Definition:</b> tensorNet.h:477</div></div>
<div class="ttc" id="agroup__tensorNet_html_a2dcc770a7215e2e76a8d520a36689e16"><div class="ttname"><a href="group__tensorNet.html#a2dcc770a7215e2e76a8d520a36689e16">tensorNet::GetOutputLayers</a></div><div class="ttdeci">uint32_t GetOutputLayers() const</div><div class="ttdoc">Retrieve the number of output layers to the network.</div><div class="ttdef"><b>Definition:</b> tensorNet.h:492</div></div>
<div class="ttc" id="agroup__tensorNet_html_ae49f74ff83e46112a30318fa0576cace"><div class="ttname"><a href="group__tensorNet.html#ae49f74ff83e46112a30318fa0576cace">tensorNet::EnableDebug</a></div><div class="ttdeci">void EnableDebug()</div><div class="ttdoc">Manually enable debug messages and synchronization.</div></div>
<div class="ttc" id="agroup__tensorNet_html_a75dba887061d29022b07e648770e8fb0"><div class="ttname"><a href="group__tensorNet.html#a75dba887061d29022b07e648770e8fb0">tensorNet::mBindings</a></div><div class="ttdeci">void ** mBindings</div><div class="ttdef"><b>Definition:</b> tensorNet.h:806</div></div>
<div class="ttc" id="anamespacenvinfer1_html"><div class="ttname"><a href="namespacenvinfer1.html">nvinfer1</a></div><div class="ttdef"><b>Definition:</b> tensorNet.h:27</div></div>
<div class="ttc" id="atensorNet_8h_html_a10a59554805ac7ce3905fd3540f98137"><div class="ttname"><a href="tensorNet_8h.html#a10a59554805ac7ce3905fd3540f98137">NOEXCEPT</a></div><div class="ttdeci">#define NOEXCEPT</div><div class="ttdef"><b>Definition:</b> tensorNet.h:73</div></div>
<div class="ttc" id="agroup__tensorNet_html_a0027d8b3617cfc905465925dd6d84b0f"><div class="ttname"><a href="group__tensorNet.html#a0027d8b3617cfc905465925dd6d84b0f">tensorNet::mMaxBatchSize</a></div><div class="ttdeci">uint32_t mMaxBatchSize</div><div class="ttdef"><b>Definition:</b> tensorNet.h:802</div></div>
<div class="ttc" id="agroup__tensorNet_html_ggae34d45c0faa674ef4cc0fbfc8fae5809a1fbcfa83e963d20d06f7c633bb2e4904"><div class="ttname"><a href="group__tensorNet.html#ggae34d45c0faa674ef4cc0fbfc8fae5809a1fbcfa83e963d20d06f7c633bb2e4904">PROFILER_POSTPROCESS</a></div><div class="ttdeci">@ PROFILER_POSTPROCESS</div><div class="ttdef"><b>Definition:</b> tensorNet.h:191</div></div>
<div class="ttc" id="agroup__tensorNet_html_a214a92c41dcdcb58b3cd8496aac0857a"><div class="ttname"><a href="group__tensorNet.html#a214a92c41dcdcb58b3cd8496aac0857a">tensorNet::GetInputHeight</a></div><div class="ttdeci">uint32_t GetInputHeight(uint32_t layer=0) const</div><div class="ttdoc">Retrieve the height of network input layer.</div><div class="ttdef"><b>Definition:</b> tensorNet.h:507</div></div>
<div class="ttc" id="agroup__tensorNet_html_a57cacfea82e9329c2cf776837dd00aef"><div class="ttname"><a href="group__tensorNet.html#a57cacfea82e9329c2cf776837dd00aef">tensorNet::LoadClassLabels</a></div><div class="ttdeci">static bool LoadClassLabels(const char *filename, std::vector&lt; std::string &gt; &amp;descriptions, int expectedClasses=-1)</div><div class="ttdoc">Load class descriptions from a label file.</div></div>
<div class="ttc" id="agroup__tensorNet_html_a7a898dfb2553869cdc318ecb03e153f1"><div class="ttname"><a href="group__tensorNet.html#a7a898dfb2553869cdc318ecb03e153f1">tensorNet::ConfigureBuilder</a></div><div class="ttdeci">bool ConfigureBuilder(nvinfer1::IBuilder *builder, uint32_t maxBatchSize, uint32_t workspaceSize, precisionType precision, deviceType device, bool allowGPUFallback, nvinfer1::IInt8Calibrator *calibrator)</div><div class="ttdoc">Configure builder options.</div></div>
<div class="ttc" id="agroup__tensorNet_html_ga70317416490f79e0150e9c4f46444116"><div class="ttname"><a href="group__tensorNet.html#ga70317416490f79e0150e9c4f46444116">precisionTypeFromStr</a></div><div class="ttdeci">precisionType precisionTypeFromStr(const char *str)</div><div class="ttdoc">Parse the precision type from a string.</div></div>
<div class="ttc" id="agroup__tensorNet_html_aaa9ac0fae88a426f1a5325886da3b009"><div class="ttname"><a href="group__tensorNet.html#aaa9ac0fae88a426f1a5325886da3b009">tensorNet::mCacheEnginePath</a></div><div class="ttdeci">std::string mCacheEnginePath</div><div class="ttdef"><b>Definition:</b> tensorNet.h:783</div></div>
<div class="ttc" id="agroup__tensorNet_html_ad266f93035a80dca80cd84d971e4f69b"><div class="ttname"><a href="group__tensorNet.html#ad266f93035a80dca80cd84d971e4f69b">tensorNet::GetProfilerTime</a></div><div class="ttdeci">float2 GetProfilerTime(profilerQuery query)</div><div class="ttdoc">Retrieve the profiler runtime (in milliseconds).</div><div class="ttdef"><b>Definition:</b> tensorNet.h:562</div></div>
<div class="ttc" id="agroup__tensorNet_html_ab5c88cf4590b53804ebedaa292d1402c"><div class="ttname"><a href="group__tensorNet.html#ab5c88cf4590b53804ebedaa292d1402c">tensorNet::mModelType</a></div><div class="ttdeci">modelType mModelType</div><div class="ttdef"><b>Definition:</b> tensorNet.h:789</div></div>
<div class="ttc" id="atensorNet_8h_html_a1fc0b1785ea99bd75ec83b1eeb4e6120"><div class="ttname"><a href="tensorNet_8h.html#a1fc0b1785ea99bd75ec83b1eeb4e6120">DIMS_H</a></div><div class="ttdeci">#define DIMS_H(x)</div><div class="ttdef"><b>Definition:</b> tensorNet.h:61</div></div>
<div class="ttc" id="agroup__tensorNet_html_ggaac6604fd52c6e5db82877390e0378623a1d325738f49e8e4c424ff671624e66f9"><div class="ttname"><a href="group__tensorNet.html#ggaac6604fd52c6e5db82877390e0378623a1d325738f49e8e4c424ff671624e66f9">TYPE_FASTEST</a></div><div class="ttdeci">@ TYPE_FASTEST</div><div class="ttdoc">The fastest detected precision should be use (i.e.</div><div class="ttdef"><b>Definition:</b> tensorNet.h:105</div></div>
<div class="ttc" id="agroup__tensorNet_html_a2e5a4207d90828c31255846b11a431ea"><div class="ttname"><a href="group__tensorNet.html#a2e5a4207d90828c31255846b11a431ea">tensorNet::GetOutputPtr</a></div><div class="ttdeci">float * GetOutputPtr(uint32_t layer=0) const</div><div class="ttdoc">Get the CUDA pointer to the output memory.</div><div class="ttdef"><b>Definition:</b> tensorNet.h:542</div></div>
<div class="ttc" id="aclasstensorNet_1_1Profiler_html_a55a6fd3103bcd4a57379a90eff183617"><div class="ttname"><a href="classtensorNet_1_1Profiler.html#a55a6fd3103bcd4a57379a90eff183617">tensorNet::Profiler::Profiler</a></div><div class="ttdeci">Profiler()</div><div class="ttdef"><b>Definition:</b> tensorNet.h:687</div></div>
<div class="ttc" id="agroup__tensorNet_html_a84ad901a2a0dc4aaf740d40307437b2b"><div class="ttname"><a href="group__tensorNet.html#a84ad901a2a0dc4aaf740d40307437b2b">tensorNet::mEnableDebug</a></div><div class="ttdeci">bool mEnableDebug</div><div class="ttdef"><b>Definition:</b> tensorNet.h:804</div></div>
<div class="ttc" id="agroup__tensorNet_html_adcfe61596f291e75a87d36c3771f25df"><div class="ttname"><a href="group__tensorNet.html#adcfe61596f291e75a87d36c3771f25df">tensorNet::GetInputDims</a></div><div class="ttdeci">Dims3 GetInputDims(uint32_t layer=0) const</div><div class="ttdoc">Retrieve the dimensions of network input layer.</div><div class="ttdef"><b>Definition:</b> tensorNet.h:497</div></div>
<div class="ttc" id="agroup__tensorNet_html_ggaa5d3f9981cdbd91516c1474006a80fe4a3025e0cdcbdfca820726c95f384ebf87"><div class="ttname"><a href="group__tensorNet.html#ggaa5d3f9981cdbd91516c1474006a80fe4a3025e0cdcbdfca820726c95f384ebf87">NUM_DEVICES</a></div><div class="ttdeci">@ NUM_DEVICES</div><div class="ttdoc">Number of device types defined.</div><div class="ttdef"><b>Definition:</b> tensorNet.h:135</div></div>
<div class="ttc" id="agroup__tensorNet_html_gaac6604fd52c6e5db82877390e0378623"><div class="ttname"><a href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a></div><div class="ttdeci">precisionType</div><div class="ttdoc">Enumeration for indicating the desired precision that the network should run in, if available in hard...</div><div class="ttdef"><b>Definition:</b> tensorNet.h:102</div></div>
<div class="ttc" id="agroup__tensorNet_html_ga35c5a50fb1ab97a827b18012534fd7a7"><div class="ttname"><a href="group__tensorNet.html#ga35c5a50fb1ab97a827b18012534fd7a7">deviceTypeFromStr</a></div><div class="ttdeci">deviceType deviceTypeFromStr(const char *str)</div><div class="ttdoc">Parse the device type from a string.</div></div>
<div class="ttc" id="agroup__tensorNet_html_a3c0509631176be6f9e25673cb0aa12dc"><div class="ttname"><a href="group__tensorNet.html#a3c0509631176be6f9e25673cb0aa12dc">tensorNet::SelectPrecision</a></div><div class="ttdeci">static precisionType SelectPrecision(precisionType precision, deviceType device=DEVICE_GPU, bool allowInt8=true)</div><div class="ttdoc">Resolve a desired precision to a specific one that's available.</div></div>
<div class="ttc" id="agroup__tensorNet_html_a92bb737172d26bda5f67d15346a02514"><div class="ttname"><a href="group__tensorNet.html#a92bb737172d26bda5f67d15346a02514">tensorNet::GetDevice</a></div><div class="ttdeci">deviceType GetDevice() const</div><div class="ttdoc">Retrieve the device being used for execution.</div><div class="ttdef"><b>Definition:</b> tensorNet.h:407</div></div>
<div class="ttc" id="agroup__log_html_ga923829d777617140de2576c40e3880ed"><div class="ttname"><a href="group__log.html#ga923829d777617140de2576c40e3880ed">LogWarning</a></div><div class="ttdeci">#define LogWarning(format, args...)</div><div class="ttdoc">Log a printf-style warning message (Log::WARNING)</div><div class="ttdef"><b>Definition:</b> logging.h:156</div></div>
<div class="ttc" id="agroup__tensorNet_html_ga675fb15bc5d4e2b8c4758c62adc6920d"><div class="ttname"><a href="group__tensorNet.html#ga675fb15bc5d4e2b8c4758c62adc6920d">modelTypeFromPath</a></div><div class="ttdeci">modelType modelTypeFromPath(const char *path)</div><div class="ttdoc">Parse the model format from a file path.</div></div>
<div class="ttc" id="agroup__tensorNet_html_ggaa5d3f9981cdbd91516c1474006a80fe4a63fbbad29461776cf20c2137a3d124f0"><div class="ttname"><a href="group__tensorNet.html#ggaa5d3f9981cdbd91516c1474006a80fe4a63fbbad29461776cf20c2137a3d124f0">DEVICE_DLA_1</a></div><div class="ttdeci">@ DEVICE_DLA_1</div><div class="ttdoc">Deep Learning Accelerator (DLA) Core 1 (only on Jetson Xavier)</div><div class="ttdef"><b>Definition:</b> tensorNet.h:134</div></div>
<div class="ttc" id="agroup__tensorNet_html_a7d0ec0d8504ac8b26c5ab4a6136599ca"><div class="ttname"><a href="group__tensorNet.html#a7d0ec0d8504ac8b26c5ab4a6136599ca">tensorNet::AllowGPUFallback</a></div><div class="ttdeci">bool AllowGPUFallback() const</div><div class="ttdoc">Return true if GPU fallback is enabled.</div><div class="ttdef"><b>Definition:</b> tensorNet.h:402</div></div>
<div class="ttc" id="agroup__tensorNet_html_a679b177784c85bfdba63dcd1008ff633"><div class="ttname"><a href="group__tensorNet.html#a679b177784c85bfdba63dcd1008ff633">tensorNet::SetStream</a></div><div class="ttdeci">void SetStream(cudaStream_t stream)</div><div class="ttdoc">Set the stream that the device is operating on.</div></div>
<div class="ttc" id="agroup__tensorNet_html_classtensorNet"><div class="ttname"><a href="group__tensorNet.html#classtensorNet">tensorNet</a></div><div class="ttdoc">Abstract class for loading a tensor network with TensorRT.</div><div class="ttdef"><b>Definition:</b> tensorNet.h:218</div></div>
<div class="ttc" id="agroup__tensorNet_html_ac74d7f0571b7782b945ff85fd6894044"><div class="ttname"><a href="group__tensorNet.html#ac74d7f0571b7782b945ff85fd6894044">tensorNet::GetModelPath</a></div><div class="ttdeci">const char * GetModelPath() const</div><div class="ttdoc">Retrieve the full path to model file, including the filename.</div><div class="ttdef"><b>Definition:</b> tensorNet.h:467</div></div>
<div class="ttc" id="agroup__tensorNet_html_a939a5123396b35a0dbee8d094d881d62"><div class="ttname"><a href="group__tensorNet.html#a939a5123396b35a0dbee8d094d881d62">tensorNet::mInputs</a></div><div class="ttdeci">std::vector&lt; layerInfo &gt; mInputs</div><div class="ttdef"><b>Definition:</b> tensorNet.h:818</div></div>
<div class="ttc" id="agroup__tensorNet_html_ad6d2272a2560bec119fa570438e3eb19"><div class="ttname"><a href="group__tensorNet.html#ad6d2272a2560bec119fa570438e3eb19">tensorNet::mEngine</a></div><div class="ttdeci">nvinfer1::ICudaEngine * mEngine</div><div class="ttdef"><b>Definition:</b> tensorNet.h:795</div></div>
<div class="ttc" id="agroup__tensorNet_html_a77703f2a7b59f836c93ae28811e22cb0"><div class="ttname"><a href="group__tensorNet.html#a77703f2a7b59f836c93ae28811e22cb0">tensorNet::GetOutputDims</a></div><div class="ttdeci">Dims3 GetOutputDims(uint32_t layer=0) const</div><div class="ttdoc">Retrieve the dimensions of network output layer.</div><div class="ttdef"><b>Definition:</b> tensorNet.h:522</div></div>
<div class="ttc" id="agroup__tensorNet_html_ggae34d45c0faa674ef4cc0fbfc8fae5809a624bb4adf22f078ad2804595dca02992"><div class="ttname"><a href="group__tensorNet.html#ggae34d45c0faa674ef4cc0fbfc8fae5809a624bb4adf22f078ad2804595dca02992">PROFILER_NETWORK</a></div><div class="ttdeci">@ PROFILER_NETWORK</div><div class="ttdef"><b>Definition:</b> tensorNet.h:190</div></div>
<div class="ttc" id="agroup__tensorNet_html_aac52fdcc0579c0426e21141636349dea"><div class="ttname"><a href="group__tensorNet.html#aac52fdcc0579c0426e21141636349dea">tensorNet::mEventsGPU</a></div><div class="ttdeci">cudaEvent_t mEventsGPU[PROFILER_TOTAL *2]</div><div class="ttdef"><b>Definition:</b> tensorNet.h:791</div></div>
<div class="ttc" id="atensorNet_8h_html_a7d959cb65990da8bfea3d941d6daf416"><div class="ttname"><a href="tensorNet_8h.html#a7d959cb65990da8bfea3d941d6daf416">DIMS_W</a></div><div class="ttdeci">#define DIMS_W(x)</div><div class="ttdef"><b>Definition:</b> tensorNet.h:62</div></div>
<div class="ttc" id="agroup__tensorNet_html_ggaac6604fd52c6e5db82877390e0378623a5bbefcad9ecb657a3841c2e8db6828d3"><div class="ttname"><a href="group__tensorNet.html#ggaac6604fd52c6e5db82877390e0378623a5bbefcad9ecb657a3841c2e8db6828d3">TYPE_FP32</a></div><div class="ttdeci">@ TYPE_FP32</div><div class="ttdoc">32-bit floating-point precision (FP32)</div><div class="ttdef"><b>Definition:</b> tensorNet.h:106</div></div>
<div class="ttc" id="astructtensorNet_1_1layerInfo_html_a860ac93d61e63ad80285030e6c582910"><div class="ttname"><a href="structtensorNet_1_1layerInfo.html#a860ac93d61e63ad80285030e6c582910">tensorNet::layerInfo::dims</a></div><div class="ttdeci">Dims3 dims</div><div class="ttdef"><b>Definition:</b> tensorNet.h:811</div></div>
<div class="ttc" id="agroup__tensorNet_html_gga5d4597e0e7beae7133d542e220528725a90e832c5673631bdfe24da7cd8eb52c9"><div class="ttname"><a href="group__tensorNet.html#gga5d4597e0e7beae7133d542e220528725a90e832c5673631bdfe24da7cd8eb52c9">MODEL_ONNX</a></div><div class="ttdeci">@ MODEL_ONNX</div><div class="ttdoc">ONNX.</div><div class="ttdef"><b>Definition:</b> tensorNet.h:159</div></div>
<div class="ttc" id="agroup__tensorNet_html_gae771c047f44cc49238c00d0e8af48106"><div class="ttname"><a href="group__tensorNet.html#gae771c047f44cc49238c00d0e8af48106">modelTypeToStr</a></div><div class="ttdeci">const char * modelTypeToStr(modelType type)</div><div class="ttdoc">Stringize function that returns modelType in text.</div></div>
<div class="ttc" id="agroup__tensorNet_html_ac8582b9a6099e3265da4c3f9fdf804ea"><div class="ttname"><a href="group__tensorNet.html#ac8582b9a6099e3265da4c3f9fdf804ea">tensorNet::PROFILER_END</a></div><div class="ttdeci">void PROFILER_END(profilerQuery query)</div><div class="ttdoc">End a profiling query, after the network is run.</div><div class="ttdef"><b>Definition:</b> tensorNet.h:716</div></div>
<div class="ttc" id="astructtensorNet_1_1layerInfo_html_acf10e2edd5bf25be4e484469a48ea9fc"><div class="ttname"><a href="structtensorNet_1_1layerInfo.html#acf10e2edd5bf25be4e484469a48ea9fc">tensorNet::layerInfo::CUDA</a></div><div class="ttdeci">float * CUDA</div><div class="ttdef"><b>Definition:</b> tensorNet.h:815</div></div>
<div class="ttc" id="agroup__tensorNet_html_a2c745474e60145ee826b53e294e7f478"><div class="ttname"><a href="group__tensorNet.html#a2c745474e60145ee826b53e294e7f478">tensorNet::mContext</a></div><div class="ttdeci">nvinfer1::IExecutionContext * mContext</div><div class="ttdef"><b>Definition:</b> tensorNet.h:796</div></div>
<div class="ttc" id="agroup__log_html_ga98544477d87d57d0b8e2b3ac03481785"><div class="ttname"><a href="group__log.html#ga98544477d87d57d0b8e2b3ac03481785">LogVerbose</a></div><div class="ttdeci">#define LogVerbose(format, args...)</div><div class="ttdoc">Log a printf-style verbose message (Log::VERBOSE)</div><div class="ttdef"><b>Definition:</b> logging.h:174</div></div>
<div class="ttc" id="agroup__tensorNet_html_ggaac6604fd52c6e5db82877390e0378623ad5386697191943144fa63df529e1a310"><div class="ttname"><a href="group__tensorNet.html#ggaac6604fd52c6e5db82877390e0378623ad5386697191943144fa63df529e1a310">NUM_PRECISIONS</a></div><div class="ttdeci">@ NUM_PRECISIONS</div><div class="ttdoc">Number of precision types defined.</div><div class="ttdef"><b>Definition:</b> tensorNet.h:109</div></div>
<div class="ttc" id="agroup__tensorNet_html_a164c1dcf9dcbc085c1b421855eda665f"><div class="ttname"><a href="group__tensorNet.html#a164c1dcf9dcbc085c1b421855eda665f">tensorNet::mPrecision</a></div><div class="ttdeci">precisionType mPrecision</div><div class="ttdef"><b>Definition:</b> tensorNet.h:788</div></div>
<div class="ttc" id="agroup__tensorNet_html_a2c80d46f8a01335e77e41023544102c9"><div class="ttname"><a href="group__tensorNet.html#a2c80d46f8a01335e77e41023544102c9">tensorNet::GetInputSize</a></div><div class="ttdeci">uint32_t GetInputSize(uint32_t layer=0) const</div><div class="ttdoc">Retrieve the size (in bytes) of network input layer.</div><div class="ttdef"><b>Definition:</b> tensorNet.h:512</div></div>
<div class="ttc" id="agroup__tensorNet_html_a27cf81b3fecf93d2e63a61220a54b393"><div class="ttname"><a href="group__tensorNet.html#a27cf81b3fecf93d2e63a61220a54b393">tensorNet::GetProfilerTime</a></div><div class="ttdeci">float GetProfilerTime(profilerQuery query, profilerDevice device)</div><div class="ttdoc">Retrieve the profiler runtime (in milliseconds).</div><div class="ttdef"><b>Definition:</b> tensorNet.h:567</div></div>
<div class="ttc" id="agroup__tensorNet_html_a3a8851513971d11746231d217f57b69f"><div class="ttname"><a href="group__tensorNet.html#a3a8851513971d11746231d217f57b69f">tensorNet::GetInputPtr</a></div><div class="ttdeci">float * GetInputPtr(uint32_t layer=0) const</div><div class="ttdoc">Get the CUDA pointer to the input layer's memory.</div><div class="ttdef"><b>Definition:</b> tensorNet.h:517</div></div>
<div class="ttc" id="agroup__tensorNet_html_abc88c21d81ca66f8c10d22910c995765"><div class="ttname"><a href="group__tensorNet.html#abc88c21d81ca66f8c10d22910c995765">tensorNet::mChecksumPath</a></div><div class="ttdeci">std::string mChecksumPath</div><div class="ttdef"><b>Definition:</b> tensorNet.h:785</div></div>
<div class="ttc" id="agroup__tensorNet_html_a03252bed041613fc1afb9d3cbb99663d"><div class="ttname"><a href="group__tensorNet.html#a03252bed041613fc1afb9d3cbb99663d">tensorNet::GetModelFilename</a></div><div class="ttdeci">const char * GetModelFilename() const</div><div class="ttdoc">Retrieve the filename of the file, excluding the directory.</div><div class="ttdef"><b>Definition:</b> tensorNet.h:472</div></div>
<div class="ttc" id="agroup__tensorNet_html_a2f14a2f4a4dfbb51b80f80a2e47a695c"><div class="ttname"><a href="group__tensorNet.html#a2f14a2f4a4dfbb51b80f80a2e47a695c">tensorNet::mDevice</a></div><div class="ttdeci">deviceType mDevice</div><div class="ttdef"><b>Definition:</b> tensorNet.h:787</div></div>
<div class="ttc" id="alogging_8h_html"><div class="ttname"><a href="logging_8h.html">logging.h</a></div></div>
<div class="ttc" id="agroup__tensorNet_html_ggae34d45c0faa674ef4cc0fbfc8fae5809af9132edd0371e716aed4d46e3da5e9ea"><div class="ttname"><a href="group__tensorNet.html#ggae34d45c0faa674ef4cc0fbfc8fae5809af9132edd0371e716aed4d46e3da5e9ea">PROFILER_TOTAL</a></div><div class="ttdeci">@ PROFILER_TOTAL</div><div class="ttdef"><b>Definition:</b> tensorNet.h:193</div></div>
<div class="ttc" id="astructtensorNet_1_1layerInfo_html_a3a361b4591cb1be7c1db37804d2ea405"><div class="ttname"><a href="structtensorNet_1_1layerInfo.html#a3a361b4591cb1be7c1db37804d2ea405">tensorNet::layerInfo::name</a></div><div class="ttdeci">std::string name</div><div class="ttdef"><b>Definition:</b> tensorNet.h:810</div></div>
<div class="ttc" id="agroup__tensorNet_html_a09d63a8fd906c99f8158bf9460a83c02"><div class="ttname"><a href="group__tensorNet.html#a09d63a8fd906c99f8158bf9460a83c02">tensorNet::GetOutputWidth</a></div><div class="ttdeci">uint32_t GetOutputWidth(uint32_t layer=0) const</div><div class="ttdoc">Retrieve the width of network output layer.</div><div class="ttdef"><b>Definition:</b> tensorNet.h:527</div></div>
<div class="ttc" id="agroup__tensorNet_html_gga5d4597e0e7beae7133d542e220528725af850960ce09a0b0d4b38edef40e5d0e4"><div class="ttname"><a href="group__tensorNet.html#gga5d4597e0e7beae7133d542e220528725af850960ce09a0b0d4b38edef40e5d0e4">MODEL_CAFFE</a></div><div class="ttdeci">@ MODEL_CAFFE</div><div class="ttdoc">caffemodel</div><div class="ttdef"><b>Definition:</b> tensorNet.h:158</div></div>
<div class="ttc" id="agroup__tensorNet_html_ga5a46a965749d6118e01307fd4d4865c9"><div class="ttname"><a href="group__tensorNet.html#ga5a46a965749d6118e01307fd4d4865c9">DEFAULT_MAX_BATCH_SIZE</a></div><div class="ttdeci">#define DEFAULT_MAX_BATCH_SIZE</div><div class="ttdoc">Default maximum batch size.</div><div class="ttdef"><b>Definition:</b> tensorNet.h:88</div></div>
<div class="ttc" id="agroup__tensorNet_html_a34e350ec6185277ac09ae55a79403e62"><div class="ttname"><a href="group__tensorNet.html#a34e350ec6185277ac09ae55a79403e62">tensorNet::GetStream</a></div><div class="ttdeci">cudaStream_t GetStream() const</div><div class="ttdoc">Retrieve the stream that the device is operating on.</div><div class="ttdef"><b>Definition:</b> tensorNet.h:447</div></div>
<div class="ttc" id="agroup__tensorNet_html_af4cb4b37a74806164257e9529cb8ed70"><div class="ttname"><a href="group__tensorNet.html#af4cb4b37a74806164257e9529cb8ed70">tensorNet::mEventsCPU</a></div><div class="ttdeci">timespec mEventsCPU[PROFILER_TOTAL *2]</div><div class="ttdef"><b>Definition:</b> tensorNet.h:792</div></div>
<div class="ttc" id="agroup__tensorNet_html_a545348243b65ce04047fd10d47e1716c"><div class="ttname"><a href="group__tensorNet.html#a545348243b65ce04047fd10d47e1716c">tensorNet::mProfilerQueriesUsed</a></div><div class="ttdeci">uint32_t mProfilerQueriesUsed</div><div class="ttdef"><b>Definition:</b> tensorNet.h:799</div></div>
<div class="ttc" id="agroup__tensorNet_html_ggae34d45c0faa674ef4cc0fbfc8fae5809a7f84ee2f6773727f3b11408e8b2e150e"><div class="ttname"><a href="group__tensorNet.html#ggae34d45c0faa674ef4cc0fbfc8fae5809a7f84ee2f6773727f3b11408e8b2e150e">PROFILER_PREPROCESS</a></div><div class="ttdeci">@ PROFILER_PREPROCESS</div><div class="ttdef"><b>Definition:</b> tensorNet.h:189</div></div>
<div class="ttc" id="agroup__tensorNet_html_ac583b8de1dd64b47338b4a3eb42ac166"><div class="ttname"><a href="group__tensorNet.html#ac583b8de1dd64b47338b4a3eb42ac166">tensorNet::GetInputLayers</a></div><div class="ttdeci">uint32_t GetInputLayers() const</div><div class="ttdoc">Retrieve the number of input layers to the network.</div><div class="ttdef"><b>Definition:</b> tensorNet.h:487</div></div>
<div class="ttc" id="agroup__tensorNet_html_ad19aafbfa262f9b8ffb0bff561f4d7f7"><div class="ttname"><a href="group__tensorNet.html#ad19aafbfa262f9b8ffb0bff561f4d7f7">tensorNet::~tensorNet</a></div><div class="ttdeci">virtual ~tensorNet()</div><div class="ttdoc">Destory.</div></div>
<div class="ttc" id="agroup__tensorNet_html_a4fe18908c74efda1708029ca3b04f0e8"><div class="ttname"><a href="group__tensorNet.html#a4fe18908c74efda1708029ca3b04f0e8">tensorNet::GenerateColor</a></div><div class="ttdeci">static float4 GenerateColor(uint32_t classID, float alpha=255.0f)</div><div class="ttdoc">Procedurally generate a color for a given class index with the specified alpha value.</div></div>
<div class="ttc" id="agroup__log_html_ga0f3919667d0ac0b001e44edb569d22fe"><div class="ttname"><a href="group__log.html#ga0f3919667d0ac0b001e44edb569d22fe">LogError</a></div><div class="ttdeci">#define LogError(format, args...)</div><div class="ttdoc">Log a printf-style error message (Log::ERROR)</div><div class="ttdef"><b>Definition:</b> logging.h:150</div></div>
<div class="ttc" id="agroup__tensorNet_html_a2fbc013f70b52f885867302446e0dca1"><div class="ttname"><a href="group__tensorNet.html#a2fbc013f70b52f885867302446e0dca1">tensorNet::ProfileModel</a></div><div class="ttdeci">bool ProfileModel(const std::string &amp;deployFile, const std::string &amp;modelFile, const std::vector&lt; std::string &gt; &amp;inputs, const std::vector&lt; Dims3 &gt; &amp;inputDims, const std::vector&lt; std::string &gt; &amp;outputs, uint32_t maxBatchSize, precisionType precision, deviceType device, bool allowGPUFallback, nvinfer1::IInt8Calibrator *calibrator, char **engineStream, size_t *engineSize)</div><div class="ttdoc">Create and output an optimized network model.</div></div>
<div class="ttc" id="agroup__tensorNet_html_ae2e0ae17baf6e1975aaad7a7f5c60ce9"><div class="ttname"><a href="group__tensorNet.html#ae2e0ae17baf6e1975aaad7a7f5c60ce9">tensorNet::PROFILER_QUERY</a></div><div class="ttdeci">bool PROFILER_QUERY(profilerQuery query)</div><div class="ttdoc">Query the CUDA part of a profiler query.</div><div class="ttdef"><b>Definition:</b> tensorNet.h:738</div></div>
<div class="ttc" id="agroup__tensorNet_html_a54005b86b851fa71aeb7a83d4ad32362"><div class="ttname"><a href="group__tensorNet.html#a54005b86b851fa71aeb7a83d4ad32362">tensorNet::mPrototxtPath</a></div><div class="ttdeci">std::string mPrototxtPath</div><div class="ttdef"><b>Definition:</b> tensorNet.h:779</div></div>
<div class="ttc" id="agroup__tensorNet_html_a7b87410f9133aea37b46979d543219b9"><div class="ttname"><a href="group__tensorNet.html#a7b87410f9133aea37b46979d543219b9">tensorNet::LoadClassColors</a></div><div class="ttdeci">static bool LoadClassColors(const char *filename, float4 *colors, int expectedClasses, float defaultAlpha=255.0f)</div><div class="ttdoc">Load class colors from a text file.</div></div>
<div class="ttc" id="agroup__tensorNet_html_a64fccb1894b0926e54a18fa47a271c70"><div class="ttname"><a href="group__tensorNet.html#a64fccb1894b0926e54a18fa47a271c70">tensorNet::mCacheCalibrationPath</a></div><div class="ttdeci">std::string mCacheCalibrationPath</div><div class="ttdef"><b>Definition:</b> tensorNet.h:784</div></div>
<div class="ttc" id="agroup__tensorNet_html_a0c6f7cc68ce87e0701029d40b46d1b81"><div class="ttname"><a href="group__tensorNet.html#a0c6f7cc68ce87e0701029d40b46d1b81">tensorNet::gLogger</a></div><div class="ttdeci">tensorNet::Logger gLogger</div></div>
<div class="ttc" id="agroup__tensorNet_html_a78cecfb7505be0ea59d29041abc85cbb"><div class="ttname"><a href="group__tensorNet.html#a78cecfb7505be0ea59d29041abc85cbb">tensorNet::CreateStream</a></div><div class="ttdeci">cudaStream_t CreateStream(bool nonBlocking=true)</div><div class="ttdoc">Create and use a new stream for execution.</div></div>
<div class="ttc" id="agroup__tensorNet_html_a275ce2318a63dcaafc1e0120a53fe606"><div class="ttname"><a href="group__tensorNet.html#a275ce2318a63dcaafc1e0120a53fe606">tensorNet::mInfer</a></div><div class="ttdeci">nvinfer1::IRuntime * mInfer</div><div class="ttdef"><b>Definition:</b> tensorNet.h:794</div></div>
<div class="ttc" id="agroup__tensorNet_html_a088c3bf591e45e52ec227491f6f299ad"><div class="ttname"><a href="group__tensorNet.html#a088c3bf591e45e52ec227491f6f299ad">tensorNet::PROFILER_BEGIN</a></div><div class="ttdeci">void PROFILER_BEGIN(profilerQuery query)</div><div class="ttdoc">Begin a profiling query, before network is run.</div><div class="ttdef"><b>Definition:</b> tensorNet.h:701</div></div>
<div class="ttc" id="aclasstensorNet_1_1Profiler_html"><div class="ttname"><a href="classtensorNet_1_1Profiler.html">tensorNet::Profiler</a></div><div class="ttdoc">Profiler interface for measuring layer timings.</div><div class="ttdef"><b>Definition:</b> tensorNet.h:684</div></div>
<div class="ttc" id="agroup__tensorNet_html_a49faef5920860345e503023b7c84423c"><div class="ttname"><a href="group__tensorNet.html#a49faef5920860345e503023b7c84423c">tensorNet::GetNetworkTime</a></div><div class="ttdeci">float GetNetworkTime()</div><div class="ttdoc">Retrieve the network runtime (in milliseconds).</div><div class="ttdef"><b>Definition:</b> tensorNet.h:552</div></div>
<div class="ttc" id="atimespec_8h_html"><div class="ttname"><a href="timespec_8h.html">timespec.h</a></div></div>
<div class="ttc" id="agroup__tensorNet_html_a3b5be95254ce71931305f4086f23f18a"><div class="ttname"><a href="group__tensorNet.html#a3b5be95254ce71931305f4086f23f18a">tensorNet::mProfilerQueriesDone</a></div><div class="ttdeci">uint32_t mProfilerQueriesDone</div><div class="ttdef"><b>Definition:</b> tensorNet.h:800</div></div>
<div class="ttc" id="aimageFormat_8h_html"><div class="ttname"><a href="imageFormat_8h.html">imageFormat.h</a></div></div>
<div class="ttc" id="agroup__tensorNet_html_afcdbdb26dc6e5117f867c83e635a0250"><div class="ttname"><a href="group__tensorNet.html#afcdbdb26dc6e5117f867c83e635a0250">tensorNet::mOutputs</a></div><div class="ttdeci">std::vector&lt; layerInfo &gt; mOutputs</div><div class="ttdef"><b>Definition:</b> tensorNet.h:819</div></div>
<div class="ttc" id="astructtensorNet_1_1layerInfo_html"><div class="ttname"><a href="structtensorNet_1_1layerInfo.html">tensorNet::layerInfo</a></div><div class="ttdef"><b>Definition:</b> tensorNet.h:808</div></div>
<div class="ttc" id="agroup__tensorNet_html_a7cb91e06b296431680d20e7e9fb0187d"><div class="ttname"><a href="group__tensorNet.html#a7cb91e06b296431680d20e7e9fb0187d">tensorNet::mModelPath</a></div><div class="ttdeci">std::string mModelPath</div><div class="ttdef"><b>Definition:</b> tensorNet.h:780</div></div>
<div class="ttc" id="acudaVector_8h_html_aa94774faf063d34dab6f3f374d73ea7a"><div class="ttname"><a href="cudaVector_8h.html#aa94774faf063d34dab6f3f374d73ea7a">alpha</a></div><div class="ttdeci">__device__ cudaVectorTypeInfo&lt; T &gt;::Base alpha(T vec, typename cudaVectorTypeInfo&lt; T &gt;::Base default_alpha=255)</div><div class="ttdef"><b>Definition:</b> cudaVector.h:98</div></div>
<div class="ttc" id="agroup__time_html_ga3c4b729b99d06b423956e7a3a17aaeb4"><div class="ttname"><a href="group__time.html#ga3c4b729b99d06b423956e7a3a17aaeb4">timeDiff</a></div><div class="ttdeci">void timeDiff(const timespec &amp;start, const timespec &amp;end, timespec *result)</div><div class="ttdoc">Find the difference between two timestamps.</div><div class="ttdef"><b>Definition:</b> timespec.h:73</div></div>
<div class="ttc" id="agroup__tensorNet_html_ggaac6604fd52c6e5db82877390e0378623a1a4ed47814b2f80f0e92daad5af7bc38"><div class="ttname"><a href="group__tensorNet.html#ggaac6604fd52c6e5db82877390e0378623a1a4ed47814b2f80f0e92daad5af7bc38">TYPE_DISABLED</a></div><div class="ttdeci">@ TYPE_DISABLED</div><div class="ttdoc">Unknown, unspecified, or disabled type.</div><div class="ttdef"><b>Definition:</b> tensorNet.h:104</div></div>
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